
(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 26 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 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)
t_1))
(sqrt
(-
(-
1.0
(pow
(fma
(cos (* phi2 0.5))
(sin (* phi1 0.5))
(* (cos (* phi1 0.5)) (- (sin (* phi2 0.5)))))
2.0))
t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0) + t_1)), sqrt(((1.0 - pow(fma(cos((phi2 * 0.5)), sin((phi1 * 0.5)), (cos((phi1 * 0.5)) * -sin((phi2 * 0.5)))), 2.0)) - t_1))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0) + t_1)), sqrt(Float64(Float64(1.0 - (fma(cos(Float64(phi2 * 0.5)), sin(Float64(phi1 * 0.5)), Float64(cos(Float64(phi1 * 0.5)) * Float64(-sin(Float64(phi2 * 0.5))))) ^ 2.0)) - t_1))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * (-N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision])), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - 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 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2} + t\_1}}{\sqrt{\left(1 - {\left(\mathsf{fma}\left(\cos \left(\phi_2 \cdot 0.5\right), \sin \left(\phi_1 \cdot 0.5\right), \cos \left(\phi_1 \cdot 0.5\right) \cdot \left(-\sin \left(\phi_2 \cdot 0.5\right)\right)\right)\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 66.7%
associate-*l*66.7%
Simplified66.7%
div-sub66.7%
sin-diff67.9%
Applied egg-rr67.9%
div-sub66.7%
sin-diff67.9%
Applied egg-rr81.8%
Taylor expanded in phi1 around inf 81.8%
fma-neg81.8%
*-commutative81.8%
*-commutative81.8%
distribute-rgt-neg-in81.8%
*-commutative81.8%
Simplified81.8%
Final simplification81.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (sqrt (+ t_1 (* t_0 (* t_2 t_2))))))
(if (or (<= lambda2 -3e-5) (not (<= lambda2 0.58)))
(*
R
(*
2.0
(atan2
t_3
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (sin (* phi2 0.5)) (cos (* phi1 0.5))))
2.0)))))))
(*
R
(*
2.0
(atan2
t_3
(sqrt (- (- 1.0 t_1) (* t_0 (* t_2 (sin (* lambda1 0.5))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = sqrt((t_1 + (t_0 * (t_2 * t_2))));
double tmp;
if ((lambda2 <= -3e-5) || !(lambda2 <= 0.58)) {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))) + pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (sin((phi2 * 0.5)) * cos((phi1 * 0.5)))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_3, sqrt(((1.0 - t_1) - (t_0 * (t_2 * sin((lambda1 * 0.5))))))));
}
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 = cos(phi1) * cos(phi2)
t_1 = ((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = sqrt((t_1 + (t_0 * (t_2 * t_2))))
if ((lambda2 <= (-3d-5)) .or. (.not. (lambda2 <= 0.58d0))) then
tmp = r * (2.0d0 * atan2(t_3, sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0))) + (((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (sin((phi2 * 0.5d0)) * cos((phi1 * 0.5d0)))) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(t_3, sqrt(((1.0d0 - t_1) - (t_0 * (t_2 * sin((lambda1 * 0.5d0))))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = Math.sqrt((t_1 + (t_0 * (t_2 * t_2))));
double tmp;
if ((lambda2 <= -3e-5) || !(lambda2 <= 0.58)) {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0))) + Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.sin((phi2 * 0.5)) * Math.cos((phi1 * 0.5)))), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt(((1.0 - t_1) - (t_0 * (t_2 * Math.sin((lambda1 * 0.5))))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = math.sqrt((t_1 + (t_0 * (t_2 * t_2)))) tmp = 0 if (lambda2 <= -3e-5) or not (lambda2 <= 0.58): tmp = R * (2.0 * math.atan2(t_3, math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0))) + math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.sin((phi2 * 0.5)) * math.cos((phi1 * 0.5)))), 2.0)))))) else: tmp = R * (2.0 * math.atan2(t_3, math.sqrt(((1.0 - t_1) - (t_0 * (t_2 * math.sin((lambda1 * 0.5)))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = sqrt(Float64(t_1 + Float64(t_0 * Float64(t_2 * t_2)))) tmp = 0.0 if ((lambda2 <= -3e-5) || !(lambda2 <= 0.58)) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))) + (Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(sin(Float64(phi2 * 0.5)) * cos(Float64(phi1 * 0.5)))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(Float64(1.0 - t_1) - Float64(t_0 * Float64(t_2 * sin(Float64(lambda1 * 0.5))))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = ((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = sqrt((t_1 + (t_0 * (t_2 * t_2)))); tmp = 0.0; if ((lambda2 <= -3e-5) || ~((lambda2 <= 0.58))) tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0))) + (((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (sin((phi2 * 0.5)) * cos((phi1 * 0.5)))) ^ 2.0)))))); else tmp = R * (2.0 * atan2(t_3, sqrt(((1.0 - t_1) - (t_0 * (t_2 * sin((lambda1 * 0.5)))))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda2, -3e-5], N[Not[LessEqual[lambda2, 0.58]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] - N[(t$95$0 * N[(t$95$2 * N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \sqrt{t\_1 + t\_0 \cdot \left(t\_2 \cdot t\_2\right)}\\
\mathbf{if}\;\lambda_2 \leq -3 \cdot 10^{-5} \lor \neg \left(\lambda_2 \leq 0.58\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right) + {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \sin \left(\phi_2 \cdot 0.5\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{\left(1 - t\_1\right) - t\_0 \cdot \left(t\_2 \cdot \sin \left(\lambda_1 \cdot 0.5\right)\right)}}\right)\\
\end{array}
\end{array}
if lambda2 < -3.00000000000000008e-5 or 0.57999999999999996 < lambda2 Initial program 50.3%
associate-*l*50.2%
Simplified50.3%
div-sub50.3%
sin-diff51.9%
Applied egg-rr51.9%
div-sub50.3%
sin-diff51.9%
Applied egg-rr65.6%
Taylor expanded in lambda1 around 0 65.5%
if -3.00000000000000008e-5 < lambda2 < 0.57999999999999996Initial program 82.6%
associate-*l*82.6%
Simplified82.6%
div-sub82.6%
sin-diff83.4%
Applied egg-rr83.4%
div-sub82.6%
sin-diff83.4%
Applied egg-rr97.5%
Taylor expanded in lambda2 around 0 97.5%
Final simplification81.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (cos phi1) (cos phi2)) (* t_1 t_1))))
(if (or (<= lambda1 -1.4e-6) (not (<= lambda1 4.4e-22)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (- 1.0 t_0) t_2)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 t_2))
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (sin (* phi2 0.5)) (cos (* phi1 0.5))))
2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1);
double tmp;
if ((lambda1 <= -1.4e-6) || !(lambda1 <= 4.4e-22)) {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - t_0) - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_0 + t_2)), sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))) + pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (sin((phi2 * 0.5)) * cos((phi1 * 0.5)))), 2.0))))));
}
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) :: tmp
t_0 = ((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1)
if ((lambda1 <= (-1.4d-6)) .or. (.not. (lambda1 <= 4.4d-22))) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - t_0) - t_2))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_0 + t_2)), sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0))) + (((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (sin((phi2 * 0.5d0)) * cos((phi1 * 0.5d0)))) ** 2.0d0))))))
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 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = (Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1);
double tmp;
if ((lambda1 <= -1.4e-6) || !(lambda1 <= 4.4e-22)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - t_0) - t_2))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + t_2)), Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0))) + Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.sin((phi2 * 0.5)) * Math.cos((phi1 * 0.5)))), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = (math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1) tmp = 0 if (lambda1 <= -1.4e-6) or not (lambda1 <= 4.4e-22): tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - t_0) - t_2)))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + t_2)), math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0))) + math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.sin((phi2 * 0.5)) * math.cos((phi1 * 0.5)))), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) tmp = 0.0 if ((lambda1 <= -1.4e-6) || !(lambda1 <= 4.4e-22)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - t_0) - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + t_2)), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))) + (Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(sin(Float64(phi2 * 0.5)) * cos(Float64(phi1 * 0.5)))) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1); tmp = 0.0; if ((lambda1 <= -1.4e-6) || ~((lambda1 <= 4.4e-22))) tmp = R * (2.0 * atan2(sqrt((t_2 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - t_0) - t_2)))); else tmp = R * (2.0 * atan2(sqrt((t_0 + t_2)), sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0))) + (((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (sin((phi2 * 0.5)) * cos((phi1 * 0.5)))) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[lambda1, -1.4e-6], N[Not[LessEqual[lambda1, 4.4e-22]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$0), $MachinePrecision] - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)\\
\mathbf{if}\;\lambda_1 \leq -1.4 \cdot 10^{-6} \lor \neg \left(\lambda_1 \leq 4.4 \cdot 10^{-22}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - t\_0\right) - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_2}}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right) + {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \sin \left(\phi_2 \cdot 0.5\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if lambda1 < -1.39999999999999994e-6 or 4.4000000000000001e-22 < lambda1 Initial program 55.5%
associate-*l*55.5%
Simplified55.5%
div-sub55.5%
sin-diff56.5%
Applied egg-rr56.5%
if -1.39999999999999994e-6 < lambda1 < 4.4000000000000001e-22Initial program 77.2%
associate-*l*77.2%
Simplified77.2%
div-sub77.2%
sin-diff78.7%
Applied egg-rr78.7%
div-sub77.2%
sin-diff78.7%
Applied egg-rr98.1%
Taylor expanded in lambda1 around 0 98.0%
Final simplification77.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (sin (* phi2 0.5)) (cos (* phi1 0.5))))
2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2
(sqrt
(+
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)
(* (* (cos phi1) (cos phi2)) (* t_1 t_1))))))
(if (or (<= lambda2 -9.5e-6) (not (<= lambda2 0.58)))
(*
R
(*
2.0
(atan2
t_2
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))
t_0))))))
(*
R
(*
2.0
(atan2
t_2
(sqrt
(-
1.0
(+
t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (sin((phi2 * 0.5)) * cos((phi1 * 0.5)))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sqrt((pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0) + ((cos(phi1) * cos(phi2)) * (t_1 * t_1))));
double tmp;
if ((lambda2 <= -9.5e-6) || !(lambda2 <= 0.58)) {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))) + t_0)))));
} else {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))))))));
}
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) :: tmp
t_0 = ((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (sin((phi2 * 0.5d0)) * cos((phi1 * 0.5d0)))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = sqrt(((((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_1 * t_1))))
if ((lambda2 <= (-9.5d-6)) .or. (.not. (lambda2 <= 0.58d0))) then
tmp = r * (2.0d0 * atan2(t_2, sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0))) + t_0)))))
else
tmp = r * (2.0d0 * atan2(t_2, sqrt((1.0d0 - (t_0 + (cos(phi1) * (cos(phi2) * (sin((lambda1 * 0.5d0)) ** 2.0d0))))))))
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 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.sin((phi2 * 0.5)) * Math.cos((phi1 * 0.5)))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.sqrt((Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1))));
double tmp;
if ((lambda2 <= -9.5e-6) || !(lambda2 <= 0.58)) {
tmp = R * (2.0 * Math.atan2(t_2, Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0))) + t_0)))));
} else {
tmp = R * (2.0 * Math.atan2(t_2, Math.sqrt((1.0 - (t_0 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda1 * 0.5)), 2.0))))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.sin((phi2 * 0.5)) * math.cos((phi1 * 0.5)))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.sqrt((math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1)))) tmp = 0 if (lambda2 <= -9.5e-6) or not (lambda2 <= 0.58): tmp = R * (2.0 * math.atan2(t_2, math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0))) + t_0))))) else: tmp = R * (2.0 * math.atan2(t_2, math.sqrt((1.0 - (t_0 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda1 * 0.5)), 2.0)))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(sin(Float64(phi2 * 0.5)) * cos(Float64(phi1 * 0.5)))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sqrt(Float64((Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)))) tmp = 0.0 if ((lambda2 <= -9.5e-6) || !(lambda2 <= 0.58)) tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))) + t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (sin((phi2 * 0.5)) * cos((phi1 * 0.5)))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = sqrt(((((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_1 * t_1)))); tmp = 0.0; if ((lambda2 <= -9.5e-6) || ~((lambda2 <= 0.58))) tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0))) + t_0))))); else tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * (sin((lambda1 * 0.5)) ^ 2.0)))))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda2, -9.5e-6], N[Not[LessEqual[lambda2, 0.58]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \sin \left(\phi_2 \cdot 0.5\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sqrt{{\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)}\\
\mathbf{if}\;\lambda_2 \leq -9.5 \cdot 10^{-6} \lor \neg \left(\lambda_2 \leq 0.58\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right) + t\_0\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}\right)\right)}}\right)\\
\end{array}
\end{array}
if lambda2 < -9.5000000000000005e-6 or 0.57999999999999996 < lambda2 Initial program 50.3%
associate-*l*50.2%
Simplified50.3%
div-sub50.3%
sin-diff51.9%
Applied egg-rr51.9%
div-sub50.3%
sin-diff51.9%
Applied egg-rr65.6%
Taylor expanded in lambda1 around 0 65.5%
if -9.5000000000000005e-6 < lambda2 < 0.57999999999999996Initial program 82.6%
associate-*l*82.6%
Simplified82.6%
div-sub82.6%
sin-diff83.4%
Applied egg-rr83.4%
div-sub82.6%
sin-diff83.4%
Applied egg-rr97.5%
Taylor expanded in lambda2 around 0 97.5%
Final simplification81.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (cos phi1) (cos phi2)) (* t_1 t_1))))
(* R (* 2.0 (atan2 (sqrt (+ t_0 t_2)) (sqrt (- (- 1.0 t_0) t_2)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1);
return R * (2.0 * atan2(sqrt((t_0 + t_2)), sqrt(((1.0 - t_0) - t_2))));
}
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
t_0 = ((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1)
code = r * (2.0d0 * atan2(sqrt((t_0 + t_2)), sqrt(((1.0d0 - t_0) - t_2))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = (Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1);
return R * (2.0 * Math.atan2(Math.sqrt((t_0 + t_2)), Math.sqrt(((1.0 - t_0) - t_2))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = (math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1) return R * (2.0 * math.atan2(math.sqrt((t_0 + t_2)), math.sqrt(((1.0 - t_0) - t_2))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + t_2)), sqrt(Float64(Float64(1.0 - t_0) - t_2))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1); tmp = R * (2.0 * atan2(sqrt((t_0 + t_2)), sqrt(((1.0 - t_0) - t_2)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$0), $MachinePrecision] - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_2}}{\sqrt{\left(1 - t\_0\right) - t\_2}}\right)
\end{array}
\end{array}
Initial program 66.7%
associate-*l*66.7%
Simplified66.7%
div-sub66.7%
sin-diff67.9%
Applied egg-rr67.9%
div-sub66.7%
sin-diff67.9%
Applied egg-rr81.8%
Final simplification81.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(-
1.0
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))
t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - 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 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 66.7%
associate-*l*66.7%
Simplified66.7%
div-sub66.7%
sin-diff67.9%
Applied egg-rr67.9%
Final simplification67.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_0)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(fabs
(-
1.0
(fma
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
t_1
(pow (sin (* -0.5 (- phi2 phi1))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(fabs((1.0 - fma((0.5 + (-0.5 * cos((lambda1 - lambda2)))), t_1, pow(sin((-0.5 * (phi2 - phi1))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(abs(Float64(1.0 - fma(Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), t_1, (sin(Float64(-0.5 * Float64(phi2 - phi1))) ^ 2.0)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$1 + N[Power[N[Sin[N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left|1 - \mathsf{fma}\left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_1, {\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 66.7%
associate-*l*66.7%
Simplified66.7%
Applied egg-rr67.4%
Simplified67.4%
Final simplification67.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (pow (sin (* phi2 -0.5)) 2.0))
(t_2 (sqrt (- 1.0 (+ (* (cos phi2) t_0) t_1))))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_3 t_3))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
(if (<= phi2 -2.4e-5)
(* R (* 2.0 (atan2 (sqrt (fma (cos phi2) t_0 t_1)) t_2)))
(if (<= phi2 2.35e-5)
(*
R
(*
2.0
(atan2
t_4
(sqrt
(-
(pow (cos (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
(* R (* 2.0 (atan2 t_4 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 = pow(sin((phi2 * -0.5)), 2.0);
double t_2 = sqrt((1.0 - ((cos(phi2) * t_0) + t_1)));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = sqrt((((cos(phi1) * cos(phi2)) * (t_3 * t_3)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if (phi2 <= -2.4e-5) {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi2), t_0, t_1)), t_2));
} else if (phi2 <= 2.35e-5) {
tmp = R * (2.0 * atan2(t_4, sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_4, t_2));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(phi2 * -0.5)) ^ 2.0 t_2 = sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_0) + t_1))) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_3 * t_3)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) tmp = 0.0 if (phi2 <= -2.4e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), t_0, t_1)), t_2))); elseif (phi2 <= 2.35e-5) tmp = Float64(R * Float64(2.0 * atan(t_4, sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_4, 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[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -2.4e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + t$95$1), $MachinePrecision]], $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2.35e-5], N[(R * N[(2.0 * N[ArcTan[t$95$4 / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$4 / t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
t_2 := \sqrt{1 - \left(\cos \phi_2 \cdot t\_0 + t\_1\right)}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_3 \cdot t\_3\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
\mathbf{if}\;\phi_2 \leq -2.4 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_0, t\_1\right)}}{t\_2}\right)\\
\mathbf{elif}\;\phi_2 \leq 2.35 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_4}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_4}{t\_2}\right)\\
\end{array}
\end{array}
if phi2 < -2.4000000000000001e-5Initial program 51.3%
Taylor expanded in phi1 around 0 51.7%
Taylor expanded in phi1 around 0 52.0%
fma-define52.0%
*-commutative52.0%
Simplified52.0%
Taylor expanded in phi1 around 0 52.8%
if -2.4000000000000001e-5 < phi2 < 2.34999999999999986e-5Initial program 78.3%
associate-*l*78.3%
Simplified78.4%
Taylor expanded in phi2 around 0 78.4%
+-commutative78.4%
associate--r+78.4%
unpow278.4%
1-sub-sin78.4%
unpow278.4%
*-commutative78.4%
Simplified78.4%
if 2.34999999999999986e-5 < phi2 Initial program 56.3%
associate-*l*56.3%
Simplified56.3%
Taylor expanded in phi1 around 0 57.2%
Final simplification67.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (* (cos phi2) t_0))
(t_2 (pow (sin (* phi2 -0.5)) 2.0))
(t_3 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))
(t_4 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= phi2 -2.8e-5)
(*
R
(*
2.0
(atan2 (sqrt (fma (cos phi2) t_0 t_2)) (sqrt (- 1.0 (+ t_1 t_2))))))
(if (<= phi2 2.45e-5)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_4 t_4))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) t_3))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi1) t_1) (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_3))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = cos(phi2) * t_0;
double t_2 = pow(sin((phi2 * -0.5)), 2.0);
double t_3 = pow(sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi2 <= -2.8e-5) {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi2), t_0, t_2)), sqrt((1.0 - (t_1 + t_2)))));
} else if (phi2 <= 2.45e-5) {
tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_4 * t_4)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * t_3)))));
} else {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_1) + pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_3)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = Float64(cos(phi2) * t_0) t_2 = sin(Float64(phi2 * -0.5)) ^ 2.0 t_3 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (phi2 <= -2.8e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), t_0, t_2)), sqrt(Float64(1.0 - Float64(t_1 + t_2)))))); elseif (phi2 <= 2.45e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_4 * t_4)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_3)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * t_1) + (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_3)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -2.8e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2.45e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$4 * t$95$4), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \cos \phi_2 \cdot t\_0\\
t_2 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
t_3 := {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -2.8 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_0, t\_2\right)}}{\sqrt{1 - \left(t\_1 + t\_2\right)}}\right)\\
\mathbf{elif}\;\phi_2 \leq 2.45 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_4 \cdot t\_4\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t\_3}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot t\_1 + {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_3}}\right)\\
\end{array}
\end{array}
if phi2 < -2.79999999999999996e-5Initial program 51.3%
Taylor expanded in phi1 around 0 51.7%
Taylor expanded in phi1 around 0 52.0%
fma-define52.0%
*-commutative52.0%
Simplified52.0%
Taylor expanded in phi1 around 0 52.8%
if -2.79999999999999996e-5 < phi2 < 2.45e-5Initial program 78.3%
associate-*l*78.3%
Simplified78.4%
Taylor expanded in phi2 around 0 78.4%
+-commutative78.4%
associate--r+78.4%
unpow278.4%
1-sub-sin78.4%
unpow278.4%
*-commutative78.4%
Simplified78.4%
if 2.45e-5 < phi2 Initial program 56.3%
associate-*l*56.3%
Simplified56.3%
Taylor expanded in phi1 around 0 57.2%
+-commutative57.2%
associate--r+57.2%
unpow257.2%
1-sub-sin57.2%
unpow257.2%
sub-neg57.2%
mul-1-neg57.2%
distribute-lft-in57.2%
metadata-eval57.2%
associate-*r*57.2%
associate-*r*57.2%
metadata-eval57.2%
distribute-lft-in57.2%
+-commutative57.2%
Simplified57.2%
Taylor expanded in phi1 around inf 57.2%
Final simplification67.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_0)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(* t_1 (- 0.5 (* 0.5 (cos (- lambda1 lambda2))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)) - (t_1 * (0.5 - (0.5 * cos((lambda1 - lambda2)))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)) - (t_1 * (0.5d0 - (0.5d0 * cos((lambda1 - lambda2)))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt(((t_1 * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)) - (t_1 * (0.5 - (0.5 * Math.cos((lambda1 - lambda2)))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt(((t_1 * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)) - (t_1 * (0.5 - (0.5 * math.cos((lambda1 - lambda2)))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) - Float64(t_1 * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0)) - (t_1 * (0.5 - (0.5 * cos((lambda1 - lambda2))))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) - t\_1 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)}}\right)
\end{array}
\end{array}
Initial program 66.7%
associate-*l*66.7%
Simplified66.7%
cancel-sign-sub-inv66.7%
div-inv66.7%
metadata-eval66.7%
sqr-sin-a66.7%
cos-266.7%
cos-sum66.7%
add-log-exp20.9%
add-log-exp20.9%
sum-log20.9%
exp-sqrt20.9%
exp-sqrt20.9%
Applied egg-rr66.7%
Final simplification66.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (sin (* 0.5 (- phi1 phi2)))))
(if (or (<= phi1 -0.16) (not (<= phi1 8.5e+33)))
(*
R
(*
2.0
(atan2
(pow (pow (cbrt t_1) 2.0) 1.5)
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(pow t_1 2.0)))
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sin((0.5 * (phi1 - phi2)));
double tmp;
if ((phi1 <= -0.16) || !(phi1 <= 8.5e+33)) {
tmp = R * (2.0 * atan2(pow(pow(cbrt(t_1), 2.0), 1.5), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0))) + pow(t_1, 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
return tmp;
}
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.sin((0.5 * (phi1 - phi2)));
double tmp;
if ((phi1 <= -0.16) || !(phi1 <= 8.5e+33)) {
tmp = R * (2.0 * Math.atan2(Math.pow(Math.pow(Math.cbrt(t_1), 2.0), 1.5), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + Math.pow(t_1, 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) tmp = 0.0 if ((phi1 <= -0.16) || !(phi1 <= 8.5e+33)) tmp = Float64(R * Float64(2.0 * atan(((cbrt(t_1) ^ 2.0) ^ 1.5), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))) + (t_1 ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -0.16], N[Not[LessEqual[phi1, 8.5e+33]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[Power[t$95$1, 1/3], $MachinePrecision], 2.0], $MachinePrecision], 1.5], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
\mathbf{if}\;\phi_1 \leq -0.16 \lor \neg \left(\phi_1 \leq 8.5 \cdot 10^{+33}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\sqrt[3]{t\_1}\right)}^{2}\right)}^{1.5}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right) + {t\_1}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi1 < -0.160000000000000003 or 8.4999999999999998e33 < phi1 Initial program 54.7%
Taylor expanded in lambda2 around 0 43.6%
Taylor expanded in lambda1 around 0 16.0%
*-commutative11.3%
add-cube-cbrt11.3%
unpow311.3%
sqr-pow10.0%
pow-prod-down21.1%
pow221.1%
*-commutative21.1%
metadata-eval21.1%
Applied egg-rr34.3%
if -0.160000000000000003 < phi1 < 8.4999999999999998e33Initial program 77.1%
associate-*l*77.1%
Simplified77.1%
Taylor expanded in phi1 around 0 75.9%
+-commutative75.9%
associate--r+76.0%
unpow276.0%
1-sub-sin75.9%
unpow275.9%
sub-neg75.9%
mul-1-neg75.9%
distribute-lft-in75.9%
metadata-eval75.9%
associate-*r*75.9%
associate-*r*75.9%
metadata-eval75.9%
distribute-lft-in75.9%
+-commutative75.9%
Simplified75.9%
Taylor expanded in phi1 around inf 75.9%
Final simplification56.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (* phi2 -0.5)) 2.0)))
(if (or (<= phi1 -0.165) (not (<= phi1 1.75e+30)))
(*
R
(*
2.0
(atan2
(pow (pow (cbrt (sin (* 0.5 (- phi1 phi2)))) 2.0) 1.5)
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_1 (* (* (cos phi1) (cos phi2)) t_1))))))))
(*
R
(*
2.0
(atan2
(sqrt (fma (cos phi2) t_0 t_2))
(sqrt (- 1.0 (+ (* (cos phi2) t_0) t_2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin((phi2 * -0.5)), 2.0);
double tmp;
if ((phi1 <= -0.165) || !(phi1 <= 1.75e+30)) {
tmp = R * (2.0 * atan2(pow(pow(cbrt(sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * ((cos(phi1) * cos(phi2)) * t_1)))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi2), t_0, t_2)), sqrt((1.0 - ((cos(phi2) * t_0) + t_2)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(phi2 * -0.5)) ^ 2.0 tmp = 0.0 if ((phi1 <= -0.165) || !(phi1 <= 1.75e+30)) tmp = Float64(R * Float64(2.0 * atan(((cbrt(sin(Float64(0.5 * Float64(phi1 - phi2)))) ^ 2.0) ^ 1.5), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), t_0, t_2)), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_0) + t_2)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -0.165], N[Not[LessEqual[phi1, 1.75e+30]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision], 1.5], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -0.165 \lor \neg \left(\phi_1 \leq 1.75 \cdot 10^{+30}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\sqrt[3]{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}\right)}^{2}\right)}^{1.5}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_0, t\_2\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_0 + t\_2\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -0.165000000000000008 or 1.75000000000000011e30 < phi1 Initial program 54.7%
Taylor expanded in lambda2 around 0 43.6%
Taylor expanded in lambda1 around 0 16.0%
*-commutative11.3%
add-cube-cbrt11.3%
unpow311.3%
sqr-pow10.0%
pow-prod-down21.1%
pow221.1%
*-commutative21.1%
metadata-eval21.1%
Applied egg-rr34.3%
if -0.165000000000000008 < phi1 < 1.75000000000000011e30Initial program 77.1%
Taylor expanded in phi1 around 0 76.2%
Taylor expanded in phi1 around 0 74.7%
fma-define74.7%
*-commutative74.7%
Simplified74.7%
Taylor expanded in phi1 around 0 74.6%
Final simplification55.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
(if (or (<= t_0 -0.04) (not (<= t_0 0.0544)))
(*
R
(*
2.0
(atan2
t_1
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))
(* R (* 2.0 (atan2 t_1 (sqrt (pow (cos (* phi2 -0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if ((t_0 <= -0.04) || !(t_0 <= 0.0544)) {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt(pow(cos((phi2 * -0.5)), 2.0))));
}
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) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)))
if ((t_0 <= (-0.04d0)) .or. (.not. (t_0 <= 0.0544d0))) then
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt((cos((phi2 * (-0.5d0))) ** 2.0d0))))
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.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if ((t_0 <= -0.04) || !(t_0 <= 0.0544)) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt(Math.pow(Math.cos((phi2 * -0.5)), 2.0))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))) tmp = 0 if (t_0 <= -0.04) or not (t_0 <= 0.0544): tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt(math.pow(math.cos((phi2 * -0.5)), 2.0)))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) tmp = 0.0 if ((t_0 <= -0.04) || !(t_0 <= 0.0544)) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt((cos(Float64(phi2 * -0.5)) ^ 2.0))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))); tmp = 0.0; if ((t_0 <= -0.04) || ~((t_0 <= 0.0544))) tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); else tmp = R * (2.0 * atan2(t_1, sqrt((cos((phi2 * -0.5)) ^ 2.0)))); 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[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[t$95$0, -0.04], N[Not[LessEqual[t$95$0, 0.0544]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
\mathbf{if}\;t\_0 \leq -0.04 \lor \neg \left(t\_0 \leq 0.0544\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0400000000000000008 or 0.054399999999999997 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 60.9%
associate-*l*60.9%
Simplified60.9%
Taylor expanded in phi1 around 0 47.9%
+-commutative47.9%
associate--r+47.9%
unpow247.9%
1-sub-sin47.9%
unpow247.9%
sub-neg47.9%
mul-1-neg47.9%
distribute-lft-in47.9%
metadata-eval47.9%
associate-*r*47.9%
associate-*r*47.9%
metadata-eval47.9%
distribute-lft-in47.9%
+-commutative47.9%
Simplified47.9%
Taylor expanded in phi2 around 0 34.4%
if -0.0400000000000000008 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.054399999999999997Initial program 83.1%
associate-*l*83.1%
Simplified83.1%
Taylor expanded in phi1 around 0 58.4%
+-commutative58.4%
associate--r+58.4%
unpow258.4%
1-sub-sin58.4%
unpow258.4%
sub-neg58.4%
mul-1-neg58.4%
distribute-lft-in58.4%
metadata-eval58.4%
associate-*r*58.4%
associate-*r*58.4%
metadata-eval58.4%
distribute-lft-in58.4%
+-commutative58.4%
Simplified58.4%
Taylor expanded in lambda2 around 0 57.4%
*-commutative57.4%
Simplified57.4%
Taylor expanded in lambda1 around 0 54.9%
*-commutative54.9%
Simplified54.9%
Final simplification39.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(if (or (<= phi1 -2.3e-10) (not (<= phi1 1.05e+34)))
(*
R
(*
2.0
(atan2
(pow (pow (cbrt (sin (* 0.5 (- phi1 phi2)))) 2.0) 1.5)
(sqrt
(-
1.0
(+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_0))))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_0)) (- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double tmp;
if ((phi1 <= -2.3e-10) || !(phi1 <= 1.05e+34)) {
tmp = R * (2.0 * atan2(pow(pow(cbrt(sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double tmp;
if ((phi1 <= -2.3e-10) || !(phi1 <= 1.05e+34)) {
tmp = R * (2.0 * Math.atan2(Math.pow(Math.pow(Math.cbrt(Math.sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_1 * (t_0 * t_0)) + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((lambda1 * 0.5)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi1 <= -2.3e-10) || !(phi1 <= 1.05e+34)) tmp = Float64(R * Float64(2.0 * atan(((cbrt(sin(Float64(0.5 * Float64(phi1 - phi2)))) ^ 2.0) ^ 1.5), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_0)))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_0)) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi1, -2.3e-10], N[Not[LessEqual[phi1, 1.05e+34]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision], 1.5], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_1 \leq -2.3 \cdot 10^{-10} \lor \neg \left(\phi_1 \leq 1.05 \cdot 10^{+34}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\sqrt[3]{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}\right)}^{2}\right)}^{1.5}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_0\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_0\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi1 < -2.30000000000000007e-10 or 1.05000000000000009e34 < phi1 Initial program 56.2%
Taylor expanded in lambda2 around 0 43.6%
Taylor expanded in lambda1 around 0 15.3%
*-commutative10.8%
add-cube-cbrt10.8%
unpow310.8%
sqr-pow9.6%
pow-prod-down21.5%
pow221.5%
*-commutative21.5%
metadata-eval21.5%
Applied egg-rr34.0%
if -2.30000000000000007e-10 < phi1 < 1.05000000000000009e34Initial program 76.7%
associate-*l*76.7%
Simplified76.7%
Taylor expanded in phi1 around 0 76.4%
+-commutative76.4%
associate--r+76.4%
unpow276.4%
1-sub-sin76.4%
unpow276.4%
sub-neg76.4%
mul-1-neg76.4%
distribute-lft-in76.4%
metadata-eval76.4%
associate-*r*76.4%
associate-*r*76.4%
metadata-eval76.4%
distribute-lft-in76.4%
+-commutative76.4%
Simplified76.4%
Taylor expanded in lambda2 around 0 59.7%
*-commutative59.7%
Simplified59.7%
unpow259.7%
sin-mult58.3%
div-inv58.3%
metadata-eval58.3%
div-inv58.3%
metadata-eval58.3%
div-inv58.3%
metadata-eval58.3%
div-inv58.3%
metadata-eval58.3%
Applied egg-rr58.3%
div-sub58.3%
+-inverses58.3%
cos-058.3%
metadata-eval58.3%
distribute-lft-out58.3%
metadata-eval58.3%
*-rgt-identity58.3%
Simplified58.3%
Final simplification46.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* 0.5 (- phi1 phi2))))
(t_2 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))
(t_3 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= (- lambda1 lambda2) -5e+27)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_2))))))
(if (<= (- lambda1 lambda2) 2e-61)
(*
R
(*
2.0
(atan2
(pow (pow (cbrt t_1) 2.0) 1.5)
(sqrt
(-
1.0
(+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_3 (* t_0 t_3))))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* t_3 t_3)) (pow (expm1 (log1p t_1)) 2.0)))
(sqrt (- 1.0 t_2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((0.5 * (phi1 - phi2)));
double t_2 = pow(sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((lambda1 - lambda2) <= -5e+27) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_2)))));
} else if ((lambda1 - lambda2) <= 2e-61) {
tmp = R * (2.0 * atan2(pow(pow(cbrt(t_1), 2.0), 1.5), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_3 * (t_0 * t_3)))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_3 * t_3)) + pow(expm1(log1p(t_1)), 2.0))), sqrt((1.0 - t_2))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.sin((0.5 * (phi1 - phi2)));
double t_2 = Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_3 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((lambda1 - lambda2) <= -5e+27) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * t_2)))));
} else if ((lambda1 - lambda2) <= 2e-61) {
tmp = R * (2.0 * Math.atan2(Math.pow(Math.pow(Math.cbrt(t_1), 2.0), 1.5), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_3 * (t_0 * t_3)))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_3 * t_3)) + Math.pow(Math.expm1(Math.log1p(t_1)), 2.0))), Math.sqrt((1.0 - t_2))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_2 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (Float64(lambda1 - lambda2) <= -5e+27) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_2)))))); elseif (Float64(lambda1 - lambda2) <= 2e-61) tmp = Float64(R * Float64(2.0 * atan(((cbrt(t_1) ^ 2.0) ^ 1.5), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_3 * Float64(t_0 * t_3)))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_3 * t_3)) + (expm1(log1p(t_1)) ^ 2.0))), sqrt(Float64(1.0 - t_2))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -5e+27], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 2e-61], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[Power[t$95$1, 1/3], $MachinePrecision], 2.0], $MachinePrecision], 1.5], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$3 * N[(t$95$0 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision] + N[Power[N[(Exp[N[Log[1 + t$95$1], $MachinePrecision]] - 1), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_2 := {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -5 \cdot 10^{+27}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_2}}\right)\\
\mathbf{elif}\;\lambda_1 - \lambda_2 \leq 2 \cdot 10^{-61}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\sqrt[3]{t\_1}\right)}^{2}\right)}^{1.5}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_3 \cdot \left(t\_0 \cdot t\_3\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_3 \cdot t\_3\right) + {\left(\mathsf{expm1}\left(\mathsf{log1p}\left(t\_1\right)\right)\right)}^{2}}}{\sqrt{1 - t\_2}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -4.99999999999999979e27Initial program 57.5%
associate-*l*57.5%
Simplified57.5%
Taylor expanded in phi1 around 0 45.3%
+-commutative45.3%
associate--r+45.3%
unpow245.3%
1-sub-sin45.2%
unpow245.2%
sub-neg45.2%
mul-1-neg45.2%
distribute-lft-in45.2%
metadata-eval45.2%
associate-*r*45.2%
associate-*r*45.2%
metadata-eval45.2%
distribute-lft-in45.2%
+-commutative45.2%
Simplified45.2%
Taylor expanded in phi2 around 0 34.4%
if -4.99999999999999979e27 < (-.f64 lambda1 lambda2) < 2.0000000000000001e-61Initial program 85.6%
Taylor expanded in lambda2 around 0 77.1%
Taylor expanded in lambda1 around 0 28.8%
*-commutative19.2%
add-cube-cbrt19.2%
unpow319.2%
sqr-pow17.4%
pow-prod-down45.1%
pow245.1%
*-commutative45.1%
metadata-eval45.1%
Applied egg-rr70.3%
if 2.0000000000000001e-61 < (-.f64 lambda1 lambda2) Initial program 64.8%
associate-*l*64.8%
Simplified64.8%
Taylor expanded in phi1 around 0 53.3%
+-commutative53.3%
associate--r+53.3%
unpow253.3%
1-sub-sin53.3%
unpow253.3%
sub-neg53.3%
mul-1-neg53.3%
distribute-lft-in53.3%
metadata-eval53.3%
associate-*r*53.3%
associate-*r*53.3%
metadata-eval53.3%
distribute-lft-in53.3%
+-commutative53.3%
Simplified53.3%
pow153.3%
metadata-eval53.3%
sqrt-pow153.3%
expm1-log1p-u53.2%
sqrt-pow153.2%
metadata-eval53.2%
pow153.2%
div-inv53.2%
metadata-eval53.2%
Applied egg-rr53.2%
Taylor expanded in phi2 around 0 38.9%
Final simplification44.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))
(t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_3 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= (- lambda1 lambda2) -5e+27)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_1))))))
(if (<= (- lambda1 lambda2) 2e-61)
(*
R
(*
2.0
(atan2
(pow (pow (cbrt (sin (* 0.5 (- phi1 phi2)))) 2.0) 1.5)
(sqrt (- 1.0 (+ t_2 (* t_3 (* t_0 t_3))))))))
(*
R
(*
2.0
(atan2 (sqrt (+ (* t_0 (* t_3 t_3)) t_2)) (sqrt (- 1.0 t_1)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((lambda1 - lambda2) <= -5e+27) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_1)))));
} else if ((lambda1 - lambda2) <= 2e-61) {
tmp = R * (2.0 * atan2(pow(pow(cbrt(sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), sqrt((1.0 - (t_2 + (t_3 * (t_0 * t_3)))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_3 * t_3)) + t_2)), sqrt((1.0 - t_1))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((lambda1 - lambda2) <= -5e+27) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * t_1)))));
} else if ((lambda1 - lambda2) <= 2e-61) {
tmp = R * (2.0 * Math.atan2(Math.pow(Math.pow(Math.cbrt(Math.sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), Math.sqrt((1.0 - (t_2 + (t_3 * (t_0 * t_3)))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_3 * t_3)) + t_2)), Math.sqrt((1.0 - t_1))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 t_2 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (Float64(lambda1 - lambda2) <= -5e+27) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_1)))))); elseif (Float64(lambda1 - lambda2) <= 2e-61) tmp = Float64(R * Float64(2.0 * atan(((cbrt(sin(Float64(0.5 * Float64(phi1 - phi2)))) ^ 2.0) ^ 1.5), sqrt(Float64(1.0 - Float64(t_2 + Float64(t_3 * Float64(t_0 * t_3)))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_3 * t_3)) + t_2)), sqrt(Float64(1.0 - t_1))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -5e+27], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 2e-61], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision], 1.5], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 + N[(t$95$3 * N[(t$95$0 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -5 \cdot 10^{+27}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_1}}\right)\\
\mathbf{elif}\;\lambda_1 - \lambda_2 \leq 2 \cdot 10^{-61}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\sqrt[3]{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}\right)}^{2}\right)}^{1.5}}{\sqrt{1 - \left(t\_2 + t\_3 \cdot \left(t\_0 \cdot t\_3\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_3 \cdot t\_3\right) + t\_2}}{\sqrt{1 - t\_1}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -4.99999999999999979e27Initial program 57.5%
associate-*l*57.5%
Simplified57.5%
Taylor expanded in phi1 around 0 45.3%
+-commutative45.3%
associate--r+45.3%
unpow245.3%
1-sub-sin45.2%
unpow245.2%
sub-neg45.2%
mul-1-neg45.2%
distribute-lft-in45.2%
metadata-eval45.2%
associate-*r*45.2%
associate-*r*45.2%
metadata-eval45.2%
distribute-lft-in45.2%
+-commutative45.2%
Simplified45.2%
Taylor expanded in phi2 around 0 34.4%
if -4.99999999999999979e27 < (-.f64 lambda1 lambda2) < 2.0000000000000001e-61Initial program 85.6%
Taylor expanded in lambda2 around 0 77.1%
Taylor expanded in lambda1 around 0 28.8%
*-commutative19.2%
add-cube-cbrt19.2%
unpow319.2%
sqr-pow17.4%
pow-prod-down45.1%
pow245.1%
*-commutative45.1%
metadata-eval45.1%
Applied egg-rr70.3%
if 2.0000000000000001e-61 < (-.f64 lambda1 lambda2) Initial program 64.8%
associate-*l*64.8%
Simplified64.8%
Taylor expanded in phi1 around 0 53.3%
+-commutative53.3%
associate--r+53.3%
unpow253.3%
1-sub-sin53.3%
unpow253.3%
sub-neg53.3%
mul-1-neg53.3%
distribute-lft-in53.3%
metadata-eval53.3%
associate-*r*53.3%
associate-*r*53.3%
metadata-eval53.3%
distribute-lft-in53.3%
+-commutative53.3%
Simplified53.3%
Taylor expanded in phi2 around 0 38.9%
Final simplification44.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (or (<= (- lambda1 lambda2) -5e+27)
(not (<= (- lambda1 lambda2) 2e-61)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* t_1 t_1)) t_2))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))
(*
R
(*
2.0
(atan2
(pow (pow (cbrt (sin (* 0.5 (- phi1 phi2)))) 2.0) 1.5)
(sqrt (- 1.0 (+ t_2 (* t_1 (* t_0 t_1)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (((lambda1 - lambda2) <= -5e+27) || !((lambda1 - lambda2) <= 2e-61)) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_1)) + t_2)), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(pow(pow(cbrt(sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), sqrt((1.0 - (t_2 + (t_1 * (t_0 * t_1)))))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (((lambda1 - lambda2) <= -5e+27) || !((lambda1 - lambda2) <= 2e-61)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_1 * t_1)) + t_2)), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.pow(Math.pow(Math.cbrt(Math.sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), Math.sqrt((1.0 - (t_2 + (t_1 * (t_0 * t_1)))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if ((Float64(lambda1 - lambda2) <= -5e+27) || !(Float64(lambda1 - lambda2) <= 2e-61)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_1 * t_1)) + t_2)), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(((cbrt(sin(Float64(0.5 * Float64(phi1 - phi2)))) ^ 2.0) ^ 1.5), sqrt(Float64(1.0 - Float64(t_2 + Float64(t_1 * Float64(t_0 * t_1)))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -5e+27], N[Not[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 2e-61]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision], 1.5], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 + N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -5 \cdot 10^{+27} \lor \neg \left(\lambda_1 - \lambda_2 \leq 2 \cdot 10^{-61}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_1 \cdot t\_1\right) + t\_2}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\sqrt[3]{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}\right)}^{2}\right)}^{1.5}}{\sqrt{1 - \left(t\_2 + t\_1 \cdot \left(t\_0 \cdot t\_1\right)\right)}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -4.99999999999999979e27 or 2.0000000000000001e-61 < (-.f64 lambda1 lambda2) Initial program 61.3%
associate-*l*61.3%
Simplified61.3%
Taylor expanded in phi1 around 0 49.4%
+-commutative49.4%
associate--r+49.4%
unpow249.4%
1-sub-sin49.4%
unpow249.4%
sub-neg49.4%
mul-1-neg49.4%
distribute-lft-in49.4%
metadata-eval49.4%
associate-*r*49.4%
associate-*r*49.4%
metadata-eval49.4%
distribute-lft-in49.4%
+-commutative49.4%
Simplified49.4%
Taylor expanded in phi2 around 0 36.6%
if -4.99999999999999979e27 < (-.f64 lambda1 lambda2) < 2.0000000000000001e-61Initial program 85.6%
Taylor expanded in lambda2 around 0 77.1%
Taylor expanded in lambda1 around 0 28.8%
*-commutative19.2%
add-cube-cbrt19.2%
unpow319.2%
sqr-pow17.4%
pow-prod-down45.1%
pow245.1%
*-commutative45.1%
metadata-eval45.1%
Applied egg-rr70.3%
Final simplification44.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -360000000000.0) (not (<= phi2 7.8e+31)))
(*
R
(*
2.0
(atan2
(pow (pow (cbrt (sin (* 0.5 (- phi1 phi2)))) 2.0) 1.5)
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi2 -0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (pow (cos (* lambda1 0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -360000000000.0) || !(phi2 <= 7.8e+31)) {
tmp = R * (2.0 * atan2(pow(pow(cbrt(sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), sqrt((1.0 - ((cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi2 * -0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(pow(cos((lambda1 * 0.5)), 2.0))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -360000000000.0) || !(phi2 <= 7.8e+31)) {
tmp = R * (2.0 * Math.atan2(Math.pow(Math.pow(Math.cbrt(Math.sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(Math.pow(Math.cos((lambda1 * 0.5)), 2.0))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -360000000000.0) || !(phi2 <= 7.8e+31)) tmp = Float64(R * Float64(2.0 * atan(((cbrt(sin(Float64(0.5 * Float64(phi1 - phi2)))) ^ 2.0) ^ 1.5), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((cos(Float64(lambda1 * 0.5)) ^ 2.0))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -360000000000.0], N[Not[LessEqual[phi2, 7.8e+31]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision], 1.5], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -360000000000 \lor \neg \left(\phi_2 \leq 7.8 \cdot 10^{+31}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\sqrt[3]{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}\right)}^{2}\right)}^{1.5}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{{\cos \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi2 < -3.6e11 or 7.79999999999999999e31 < phi2 Initial program 54.4%
Taylor expanded in lambda2 around 0 42.0%
Taylor expanded in lambda1 around 0 13.8%
Taylor expanded in phi1 around 0 14.7%
*-commutative14.7%
add-cube-cbrt14.6%
unpow314.6%
sqr-pow13.3%
pow-prod-down31.9%
pow231.9%
*-commutative31.9%
metadata-eval31.9%
Applied egg-rr31.9%
if -3.6e11 < phi2 < 7.79999999999999999e31Initial program 75.5%
associate-*l*75.5%
Simplified75.5%
Taylor expanded in phi1 around 0 47.4%
+-commutative47.4%
associate--r+47.4%
unpow247.4%
1-sub-sin47.4%
unpow247.4%
sub-neg47.4%
mul-1-neg47.4%
distribute-lft-in47.4%
metadata-eval47.4%
associate-*r*47.4%
associate-*r*47.4%
metadata-eval47.4%
distribute-lft-in47.4%
+-commutative47.4%
Simplified47.4%
Taylor expanded in lambda2 around 0 40.1%
*-commutative40.1%
Simplified40.1%
Taylor expanded in phi2 around 0 38.6%
unpow238.6%
1-sub-sin38.7%
unpow238.7%
Simplified38.7%
Final simplification35.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
(if (<= phi2 -370000000000.0)
(*
R
(*
2.0
(atan2
(pow (pow (cbrt (sin (* 0.5 (- phi1 phi2)))) 2.0) 1.5)
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi2 -0.5)) 2.0)))))))
(if (<= phi2 3.65)
(* R (* 2.0 (atan2 t_1 (sqrt (pow (cos (* lambda1 0.5)) 2.0)))))
(* R (* 2.0 (atan2 t_1 (sqrt (pow (cos (* phi2 -0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if (phi2 <= -370000000000.0) {
tmp = R * (2.0 * atan2(pow(pow(cbrt(sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), sqrt((1.0 - ((cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi2 * -0.5)), 2.0))))));
} else if (phi2 <= 3.65) {
tmp = R * (2.0 * atan2(t_1, sqrt(pow(cos((lambda1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt(pow(cos((phi2 * -0.5)), 2.0))));
}
return tmp;
}
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.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if (phi2 <= -370000000000.0) {
tmp = R * (2.0 * Math.atan2(Math.pow(Math.pow(Math.cbrt(Math.sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
} else if (phi2 <= 3.65) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt(Math.pow(Math.cos((lambda1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt(Math.pow(Math.cos((phi2 * -0.5)), 2.0))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) tmp = 0.0 if (phi2 <= -370000000000.0) tmp = Float64(R * Float64(2.0 * atan(((cbrt(sin(Float64(0.5 * Float64(phi1 - phi2)))) ^ 2.0) ^ 1.5), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); elseif (phi2 <= 3.65) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt((cos(Float64(lambda1 * 0.5)) ^ 2.0))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt((cos(Float64(phi2 * -0.5)) ^ 2.0))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -370000000000.0], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision], 1.5], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 3.65], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[Power[N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
\mathbf{if}\;\phi_2 \leq -370000000000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\sqrt[3]{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}\right)}^{2}\right)}^{1.5}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\mathbf{elif}\;\phi_2 \leq 3.65:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi2 < -3.7e11Initial program 52.4%
Taylor expanded in lambda2 around 0 40.5%
Taylor expanded in lambda1 around 0 13.5%
Taylor expanded in phi1 around 0 14.3%
*-commutative14.3%
add-cube-cbrt14.3%
unpow314.3%
sqr-pow12.6%
pow-prod-down32.2%
pow232.2%
*-commutative32.2%
metadata-eval32.2%
Applied egg-rr32.2%
if -3.7e11 < phi2 < 3.64999999999999991Initial program 76.2%
associate-*l*76.2%
Simplified76.2%
Taylor expanded in phi1 around 0 46.8%
+-commutative46.8%
associate--r+46.8%
unpow246.8%
1-sub-sin46.8%
unpow246.8%
sub-neg46.8%
mul-1-neg46.8%
distribute-lft-in46.8%
metadata-eval46.8%
associate-*r*46.8%
associate-*r*46.8%
metadata-eval46.8%
distribute-lft-in46.8%
+-commutative46.8%
Simplified46.8%
Taylor expanded in lambda2 around 0 39.8%
*-commutative39.8%
Simplified39.8%
Taylor expanded in phi2 around 0 39.3%
unpow239.3%
1-sub-sin39.4%
unpow239.4%
Simplified39.4%
if 3.64999999999999991 < phi2 Initial program 56.5%
associate-*l*56.5%
Simplified56.5%
Taylor expanded in phi1 around 0 57.1%
+-commutative57.1%
associate--r+57.2%
unpow257.2%
1-sub-sin57.1%
unpow257.1%
sub-neg57.1%
mul-1-neg57.1%
distribute-lft-in57.1%
metadata-eval57.1%
associate-*r*57.1%
associate-*r*57.1%
metadata-eval57.1%
distribute-lft-in57.1%
+-commutative57.1%
Simplified57.1%
Taylor expanded in lambda2 around 0 44.6%
*-commutative44.6%
Simplified44.6%
Taylor expanded in lambda1 around 0 31.4%
*-commutative31.4%
Simplified31.4%
Final simplification36.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(pow (pow (cbrt (sin (* 0.5 (- phi1 phi2)))) 2.0) 1.5)
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi2 -0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(pow(pow(cbrt(sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), sqrt((1.0 - ((cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi2 * -0.5)), 2.0))))));
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.pow(Math.pow(Math.cbrt(Math.sin((0.5 * (phi1 - phi2)))), 2.0), 1.5), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(((cbrt(sin(Float64(0.5 * Float64(phi1 - phi2)))) ^ 2.0) ^ 1.5), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision], 1.5], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\sqrt[3]{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}\right)}^{2}\right)}^{1.5}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)
\end{array}
Initial program 66.7%
Taylor expanded in lambda2 around 0 48.4%
Taylor expanded in lambda1 around 0 14.2%
Taylor expanded in phi1 around 0 12.1%
*-commutative12.1%
add-cube-cbrt12.1%
unpow312.1%
sqr-pow10.5%
pow-prod-down24.2%
pow224.2%
*-commutative24.2%
metadata-eval24.2%
Applied egg-rr24.2%
Final simplification24.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (cos (* phi2 -0.5)))
(t_2 (sin (* phi2 -0.5))))
(if (<= phi1 5.5e-85)
(*
R
(*
2.0
(atan2
(* phi1 (- (* 0.5 (- t_1)) (/ t_2 phi1)))
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))))))))
(*
R
(*
2.0
(atan2
(+ t_2 (* 0.5 (* phi1 t_1)))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow t_2 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos((phi2 * -0.5));
double t_2 = sin((phi2 * -0.5));
double tmp;
if (phi1 <= 5.5e-85) {
tmp = R * (2.0 * atan2((phi1 * ((0.5 * -t_1) - (t_2 / phi1))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))))));
} else {
tmp = R * (2.0 * atan2((t_2 + (0.5 * (phi1 * t_1))), sqrt((1.0 - ((cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(t_2, 2.0))))));
}
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) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos((phi2 * (-0.5d0)))
t_2 = sin((phi2 * (-0.5d0)))
if (phi1 <= 5.5d-85) then
tmp = r * (2.0d0 * atan2((phi1 * ((0.5d0 * -t_1) - (t_2 / phi1))), sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))))))
else
tmp = r * (2.0d0 * atan2((t_2 + (0.5d0 * (phi1 * t_1))), sqrt((1.0d0 - ((cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)) + (t_2 ** 2.0d0))))))
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.cos((phi2 * -0.5));
double t_2 = Math.sin((phi2 * -0.5));
double tmp;
if (phi1 <= 5.5e-85) {
tmp = R * (2.0 * Math.atan2((phi1 * ((0.5 * -t_1) - (t_2 / phi1))), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))))));
} else {
tmp = R * (2.0 * Math.atan2((t_2 + (0.5 * (phi1 * t_1))), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(t_2, 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos((phi2 * -0.5)) t_2 = math.sin((phi2 * -0.5)) tmp = 0 if phi1 <= 5.5e-85: tmp = R * (2.0 * math.atan2((phi1 * ((0.5 * -t_1) - (t_2 / phi1))), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0))))))) else: tmp = R * (2.0 * math.atan2((t_2 + (0.5 * (phi1 * t_1))), math.sqrt((1.0 - ((math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + math.pow(t_2, 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = cos(Float64(phi2 * -0.5)) t_2 = sin(Float64(phi2 * -0.5)) tmp = 0.0 if (phi1 <= 5.5e-85) tmp = Float64(R * Float64(2.0 * atan(Float64(phi1 * Float64(Float64(0.5 * Float64(-t_1)) - Float64(t_2 / phi1))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))))))); else tmp = Float64(R * Float64(2.0 * atan(Float64(t_2 + Float64(0.5 * Float64(phi1 * t_1))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (t_2 ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos((phi2 * -0.5)); t_2 = sin((phi2 * -0.5)); tmp = 0.0; if (phi1 <= 5.5e-85) tmp = R * (2.0 * atan2((phi1 * ((0.5 * -t_1) - (t_2 / phi1))), sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0))))))); else tmp = R * (2.0 * atan2((t_2 + (0.5 * (phi1 * t_1))), sqrt((1.0 - ((cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)) + (t_2 ^ 2.0)))))); 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[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, 5.5e-85], N[(R * N[(2.0 * N[ArcTan[N[(phi1 * N[(N[(0.5 * (-t$95$1)), $MachinePrecision] - N[(t$95$2 / phi1), $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] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(t$95$2 + N[(0.5 * N[(phi1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \left(\phi_2 \cdot -0.5\right)\\
t_2 := \sin \left(\phi_2 \cdot -0.5\right)\\
\mathbf{if}\;\phi_1 \leq 5.5 \cdot 10^{-85}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\phi_1 \cdot \left(0.5 \cdot \left(-t\_1\right) - \frac{t\_2}{\phi_1}\right)}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2 + 0.5 \cdot \left(\phi_1 \cdot t\_1\right)}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {t\_2}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < 5.4999999999999997e-85Initial program 70.9%
Taylor expanded in phi1 around 0 57.8%
Taylor expanded in phi1 around -inf 19.6%
if 5.4999999999999997e-85 < phi1 Initial program 58.6%
Taylor expanded in lambda2 around 0 44.6%
Taylor expanded in lambda1 around 0 15.3%
Taylor expanded in phi1 around 0 12.7%
Taylor expanded in phi1 around 0 15.8%
*-commutative15.8%
*-commutative15.8%
Simplified15.8%
Final simplification18.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2)))))
(*
R
(*
2.0
(atan2
t_0
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))
(pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
return R * (2.0 * atan2(t_0, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))) + pow(t_0, 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (phi1 - phi2)))
code = r * (2.0d0 * atan2(t_0, sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0))) + (t_0 ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (phi1 - phi2)));
return R * (2.0 * Math.atan2(t_0, Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0))) + Math.pow(t_0, 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (phi1 - phi2))) return R * (2.0 * math.atan2(t_0, math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0))) + math.pow(t_0, 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) return Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))) + (t_0 ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))); tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0))) + (t_0 ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right) + {t\_0}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 66.7%
Taylor expanded in lambda2 around 0 48.4%
Taylor expanded in lambda1 around 0 14.2%
Taylor expanded in lambda1 around 0 14.1%
Final simplification14.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2)))))
(*
R
(*
2.0
(atan2
t_0
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0)))
(pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
return R * (2.0 * atan2(t_0, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))) + pow(t_0, 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (phi1 - phi2)))
code = r * (2.0d0 * atan2(t_0, sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (sin((lambda1 * 0.5d0)) ** 2.0d0))) + (t_0 ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (phi1 - phi2)));
return R * (2.0 * Math.atan2(t_0, Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda1 * 0.5)), 2.0))) + Math.pow(t_0, 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (phi1 - phi2))) return R * (2.0 * math.atan2(t_0, math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda1 * 0.5)), 2.0))) + math.pow(t_0, 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) return Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))) + (t_0 ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))); tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (sin((lambda1 * 0.5)) ^ 2.0))) + (t_0 ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}\right) + {t\_0}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 66.7%
Taylor expanded in lambda2 around 0 48.4%
Taylor expanded in lambda1 around 0 14.2%
Taylor expanded in lambda2 around 0 14.3%
Final simplification14.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(sqrt
(+
-1.0
(-
2.0
(fma
(pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)
(cos phi2)
(pow (sin (* phi2 -0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((-1.0 + (2.0 - fma(pow(sin((-0.5 * (lambda2 - lambda1))), 2.0), cos(phi2), pow(sin((phi2 * -0.5)), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(Float64(-1.0 + Float64(2.0 - fma((sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0), cos(phi2), (sin(Float64(phi2 * -0.5)) ^ 2.0)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(-1.0 + N[(2.0 - N[(N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\sqrt{-1 + \left(2 - \mathsf{fma}\left({\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}, \cos \phi_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)\right)}}\right)
\end{array}
Initial program 66.7%
Taylor expanded in lambda2 around 0 48.4%
Taylor expanded in lambda1 around 0 14.2%
Taylor expanded in phi1 around 0 12.1%
expm1-log1p-u12.1%
fma-define12.1%
*-commutative12.1%
Applied egg-rr12.1%
Simplified12.1%
Final simplification12.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(sqrt
(+
1.0
(-
(* (cos phi2) (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5))
(pow (sin (* phi2 -0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((1.0 + ((cos(phi2) * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)) - pow(sin((phi2 * -0.5)), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), sqrt((1.0d0 + ((cos(phi2) * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0)) - (sin((phi2 * (-0.5d0))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), Math.sqrt((1.0 + ((Math.cos(phi2) * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5)) - Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), math.sqrt((1.0 + ((math.cos(phi2) * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5)) - math.pow(math.sin((phi2 * -0.5)), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(Float64(1.0 + Float64(Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5)) - (sin(Float64(phi2 * -0.5)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((1.0 + ((cos(phi2) * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)) - (sin((phi2 * -0.5)) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\sqrt{1 + \left(\cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right) - {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)
\end{array}
Initial program 66.7%
Taylor expanded in lambda2 around 0 48.4%
Taylor expanded in lambda1 around 0 14.2%
Taylor expanded in phi1 around 0 12.1%
*-commutative12.1%
metadata-eval12.1%
div-inv12.1%
pow212.1%
sin-mult12.1%
Applied egg-rr12.1%
div-sub12.1%
+-inverses12.1%
cos-012.1%
metadata-eval12.1%
associate-*r*12.1%
metadata-eval12.1%
*-lft-identity12.1%
Simplified12.1%
Final simplification12.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), sqrt((1.0d0 - (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), Math.sqrt((1.0 - Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), math.sqrt((1.0 - math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((1.0 - (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}\right)
\end{array}
Initial program 66.7%
Taylor expanded in lambda2 around 0 48.4%
Taylor expanded in lambda1 around 0 14.2%
Taylor expanded in phi1 around 0 12.1%
Taylor expanded in phi2 around 0 10.4%
Final simplification10.4%
herbie shell --seed 2024085
(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))))))))))