
(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 29 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 (cos (* phi2 0.5)))
(t_1 (sin (* 0.5 phi1)))
(t_2 (cos (- lambda1 lambda2)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (sin (/ (- lambda1 lambda2) 2.0)))
(t_5 (sin (* 0.5 (- phi1 phi2))))
(t_6 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_4 (* t_3 t_4))))
(t_7 (cos (* 0.5 phi1))))
(if (<= (atan2 (sqrt t_6) (sqrt (- 1.0 t_6))) 0.05)
(*
(atan2
(hypot
t_5
(*
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
(sqrt t_3)))
(sqrt
(-
1.0
(fma (cos phi1) (* (cos phi2) (- 0.5 (* 0.5 t_2))) (pow t_5 2.0)))))
(* R 2.0))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma t_0 t_1 (* (sin (* phi2 -0.5)) t_7)) 2.0)
(* t_3 (- 0.5 (/ t_2 2.0)))))
(sqrt
(-
(- 1.0 (pow (- (* t_0 t_1) (* t_7 (sin (* phi2 0.5)))) 2.0))
(* t_3 (* t_4 t_4))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi2 * 0.5));
double t_1 = sin((0.5 * phi1));
double t_2 = cos((lambda1 - lambda2));
double t_3 = cos(phi1) * cos(phi2);
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double t_5 = sin((0.5 * (phi1 - phi2)));
double t_6 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_4 * (t_3 * t_4));
double t_7 = cos((0.5 * phi1));
double tmp;
if (atan2(sqrt(t_6), sqrt((1.0 - t_6))) <= 0.05) {
tmp = atan2(hypot(t_5, (((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))) * sqrt(t_3))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * t_2))), pow(t_5, 2.0))))) * (R * 2.0);
} else {
tmp = R * (2.0 * atan2(sqrt((pow(fma(t_0, t_1, (sin((phi2 * -0.5)) * t_7)), 2.0) + (t_3 * (0.5 - (t_2 / 2.0))))), sqrt(((1.0 - pow(((t_0 * t_1) - (t_7 * sin((phi2 * 0.5)))), 2.0)) - (t_3 * (t_4 * t_4))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi2 * 0.5)) t_1 = sin(Float64(0.5 * phi1)) t_2 = cos(Float64(lambda1 - lambda2)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_5 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_6 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_4 * Float64(t_3 * t_4))) t_7 = cos(Float64(0.5 * phi1)) tmp = 0.0 if (atan(sqrt(t_6), sqrt(Float64(1.0 - t_6))) <= 0.05) tmp = Float64(atan(hypot(t_5, Float64(Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) * sqrt(t_3))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * t_2))), (t_5 ^ 2.0))))) * Float64(R * 2.0)); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_0, t_1, Float64(sin(Float64(phi2 * -0.5)) * t_7)) ^ 2.0) + Float64(t_3 * Float64(0.5 - Float64(t_2 / 2.0))))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_0 * t_1) - Float64(t_7 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) - Float64(t_3 * Float64(t_4 * t_4))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$4 * N[(t$95$3 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[ArcTan[N[Sqrt[t$95$6], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$6), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 0.05], N[(N[ArcTan[N[Sqrt[t$95$5 ^ 2 + N[(N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[t$95$3], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$5, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$0 * t$95$1 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$7), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$3 * N[(0.5 - N[(t$95$2 / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$0 * t$95$1), $MachinePrecision] - N[(t$95$7 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(t$95$3 * N[(t$95$4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_2 \cdot 0.5\right)\\
t_1 := \sin \left(0.5 \cdot \phi_1\right)\\
t_2 := \cos \left(\lambda_1 - \lambda_2\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_5 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_6 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_4 \cdot \left(t\_3 \cdot t\_4\right)\\
t_7 := \cos \left(0.5 \cdot \phi_1\right)\\
\mathbf{if}\;\tan^{-1}_* \frac{\sqrt{t\_6}}{\sqrt{1 - t\_6}} \leq 0.05:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(t\_5, \left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right) \cdot \sqrt{t\_3}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot t\_2\right), {t\_5}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_0, t\_1, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_7\right)\right)}^{2} + t\_3 \cdot \left(0.5 - \frac{t\_2}{2}\right)}}{\sqrt{\left(1 - {\left(t\_0 \cdot t\_1 - t\_7 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) - t\_3 \cdot \left(t\_4 \cdot t\_4\right)}}\right)\\
\end{array}
\end{array}
if (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) < 0.050000000000000003Initial program 91.5%
associate-*r*91.5%
*-commutative91.5%
Simplified91.5%
Applied egg-rr95.9%
*-lft-identity95.9%
*-commutative95.9%
*-commutative95.9%
metadata-eval95.9%
cancel-sign-sub-inv95.9%
Simplified95.9%
*-commutative95.9%
metadata-eval95.9%
div-inv95.9%
div-sub95.9%
sin-diff96.1%
Applied egg-rr96.1%
if 0.050000000000000003 < (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) Initial program 60.3%
associate-*l*60.3%
Simplified60.3%
div-sub60.3%
sin-diff61.3%
div-inv61.3%
metadata-eval61.3%
div-inv61.3%
metadata-eval61.3%
div-inv61.3%
metadata-eval61.3%
div-inv61.3%
metadata-eval61.3%
Applied egg-rr61.3%
div-sub60.3%
sin-diff61.3%
div-inv61.3%
metadata-eval61.3%
div-inv61.3%
metadata-eval61.3%
div-inv61.3%
metadata-eval61.3%
div-inv61.3%
metadata-eval61.3%
Applied egg-rr75.6%
*-commutative75.6%
*-commutative75.6%
fmm-def75.6%
*-commutative75.6%
*-commutative75.6%
*-commutative75.6%
distribute-lft-neg-in75.6%
sin-neg75.6%
distribute-rgt-neg-in75.6%
metadata-eval75.6%
*-commutative75.6%
*-commutative75.6%
Simplified75.6%
sin-mult75.6%
cos-sum75.6%
cos-275.6%
div-sub75.6%
+-inverses75.6%
Applied egg-rr75.6%
cos-075.6%
metadata-eval75.6%
Simplified75.6%
Final simplification77.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 phi1)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (cos (* phi2 0.5)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* (* (cos phi1) (cos phi2)) (* t_3 t_3))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_2 t_0 (* (sin (* phi2 -0.5)) t_1)) 2.0) t_4))
(sqrt
(-
(-
1.0
(pow (- (* t_0 (expm1 (log1p t_2))) (* t_1 (sin (* phi2 0.5)))) 2.0))
t_4)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * phi1));
double t_1 = cos((0.5 * phi1));
double t_2 = cos((phi2 * 0.5));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = (cos(phi1) * cos(phi2)) * (t_3 * t_3);
return R * (2.0 * atan2(sqrt((pow(fma(t_2, t_0, (sin((phi2 * -0.5)) * t_1)), 2.0) + t_4)), sqrt(((1.0 - pow(((t_0 * expm1(log1p(t_2))) - (t_1 * sin((phi2 * 0.5)))), 2.0)) - t_4))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi1)) t_1 = cos(Float64(0.5 * phi1)) t_2 = cos(Float64(phi2 * 0.5)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_3 * t_3)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_2, t_0, Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0) + t_4)), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_0 * expm1(log1p(t_2))) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) - t_4))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$2 * t$95$0 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$0 * N[(Exp[N[Log[1 + t$95$2], $MachinePrecision]] - 1), $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \phi_1\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \cos \left(\phi_2 \cdot 0.5\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_3 \cdot t\_3\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_2, t\_0, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_1\right)\right)}^{2} + t\_4}}{\sqrt{\left(1 - {\left(t\_0 \cdot \mathsf{expm1}\left(\mathsf{log1p}\left(t\_2\right)\right) - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) - t\_4}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified63.0%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr77.0%
*-commutative77.0%
*-commutative77.0%
fmm-def77.0%
*-commutative77.0%
*-commutative77.0%
*-commutative77.0%
distribute-lft-neg-in77.0%
sin-neg77.0%
distribute-rgt-neg-in77.0%
metadata-eval77.0%
*-commutative77.0%
*-commutative77.0%
Simplified77.0%
expm1-log1p-u77.0%
Applied egg-rr77.0%
Final simplification77.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 phi1)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (cos (* phi2 0.5)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* (* (cos phi1) (cos phi2)) (* t_3 t_3))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_2 t_0 (* (sin (* phi2 -0.5)) t_1)) 2.0) t_4))
(sqrt
(-
(-
1.0
(pow (- (* t_0 (+ (+ t_2 1.0) -1.0)) (* t_1 (sin (* phi2 0.5)))) 2.0))
t_4)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * phi1));
double t_1 = cos((0.5 * phi1));
double t_2 = cos((phi2 * 0.5));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = (cos(phi1) * cos(phi2)) * (t_3 * t_3);
return R * (2.0 * atan2(sqrt((pow(fma(t_2, t_0, (sin((phi2 * -0.5)) * t_1)), 2.0) + t_4)), sqrt(((1.0 - pow(((t_0 * ((t_2 + 1.0) + -1.0)) - (t_1 * sin((phi2 * 0.5)))), 2.0)) - t_4))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi1)) t_1 = cos(Float64(0.5 * phi1)) t_2 = cos(Float64(phi2 * 0.5)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_3 * t_3)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_2, t_0, Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0) + t_4)), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_0 * Float64(Float64(t_2 + 1.0) + -1.0)) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) - t_4))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$2 * t$95$0 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$0 * N[(N[(t$95$2 + 1.0), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \phi_1\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \cos \left(\phi_2 \cdot 0.5\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_3 \cdot t\_3\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_2, t\_0, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_1\right)\right)}^{2} + t\_4}}{\sqrt{\left(1 - {\left(t\_0 \cdot \left(\left(t\_2 + 1\right) + -1\right) - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) - t\_4}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified63.0%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr77.0%
*-commutative77.0%
*-commutative77.0%
fmm-def77.0%
*-commutative77.0%
*-commutative77.0%
*-commutative77.0%
distribute-lft-neg-in77.0%
sin-neg77.0%
distribute-rgt-neg-in77.0%
metadata-eval77.0%
*-commutative77.0%
*-commutative77.0%
Simplified77.0%
expm1-log1p-u77.0%
Applied egg-rr77.0%
expm1-undefine77.0%
log1p-undefine77.0%
rem-exp-log77.0%
*-commutative77.0%
Applied egg-rr77.0%
Final simplification77.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 phi1)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (cos (* phi2 0.5)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* (* (cos phi1) (cos phi2)) (* t_3 t_3))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_2 t_0 (* (sin (* phi2 -0.5)) t_1)) 2.0) t_4))
(sqrt
(-
(- 1.0 (pow (- (* t_2 t_0) (* t_1 (sin (* phi2 0.5)))) 2.0))
t_4)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * phi1));
double t_1 = cos((0.5 * phi1));
double t_2 = cos((phi2 * 0.5));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = (cos(phi1) * cos(phi2)) * (t_3 * t_3);
return R * (2.0 * atan2(sqrt((pow(fma(t_2, t_0, (sin((phi2 * -0.5)) * t_1)), 2.0) + t_4)), sqrt(((1.0 - pow(((t_2 * t_0) - (t_1 * sin((phi2 * 0.5)))), 2.0)) - t_4))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi1)) t_1 = cos(Float64(0.5 * phi1)) t_2 = cos(Float64(phi2 * 0.5)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_3 * t_3)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_2, t_0, Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0) + t_4)), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_2 * t_0) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) - t_4))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$2 * t$95$0 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$2 * t$95$0), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \phi_1\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \cos \left(\phi_2 \cdot 0.5\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_3 \cdot t\_3\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_2, t\_0, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_1\right)\right)}^{2} + t\_4}}{\sqrt{\left(1 - {\left(t\_2 \cdot t\_0 - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) - t\_4}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified63.0%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr77.0%
*-commutative77.0%
*-commutative77.0%
fmm-def77.0%
*-commutative77.0%
*-commutative77.0%
*-commutative77.0%
distribute-lft-neg-in77.0%
sin-neg77.0%
distribute-rgt-neg-in77.0%
metadata-eval77.0%
*-commutative77.0%
*-commutative77.0%
Simplified77.0%
Final simplification77.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos (* phi2 0.5)) (sin (* 0.5 phi1))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (cos (* 0.5 phi1)))
(t_3
(sqrt
(-
(- 1.0 (pow (- t_0 (* t_2 (sin (* phi2 0.5)))) 2.0))
(* (* (cos phi1) (cos phi2)) (* t_1 t_1)))))
(t_4 (pow (+ t_0 (* (sin (* phi2 -0.5)) t_2)) 2.0)))
(if (or (<= lambda2 -2.2e-13) (not (<= lambda2 1.95e-8)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0)))
t_4))
t_3)))
(*
R
(*
2.0
(atan2
(sqrt
(+ t_4 (* (cos phi1) (* (cos phi2) (pow (sin (* 0.5 lambda1)) 2.0)))))
t_3))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi2 * 0.5)) * sin((0.5 * phi1));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos((0.5 * phi1));
double t_3 = sqrt(((1.0 - pow((t_0 - (t_2 * sin((phi2 * 0.5)))), 2.0)) - ((cos(phi1) * cos(phi2)) * (t_1 * t_1))));
double t_4 = pow((t_0 + (sin((phi2 * -0.5)) * t_2)), 2.0);
double tmp;
if ((lambda2 <= -2.2e-13) || !(lambda2 <= 1.95e-8)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0))) + t_4)), t_3));
} else {
tmp = R * (2.0 * atan2(sqrt((t_4 + (cos(phi1) * (cos(phi2) * pow(sin((0.5 * lambda1)), 2.0))))), t_3));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = cos((phi2 * 0.5d0)) * sin((0.5d0 * phi1))
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = cos((0.5d0 * phi1))
t_3 = sqrt(((1.0d0 - ((t_0 - (t_2 * sin((phi2 * 0.5d0)))) ** 2.0d0)) - ((cos(phi1) * cos(phi2)) * (t_1 * t_1))))
t_4 = (t_0 + (sin((phi2 * (-0.5d0))) * t_2)) ** 2.0d0
if ((lambda2 <= (-2.2d-13)) .or. (.not. (lambda2 <= 1.95d-8))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 2.0d0))) + t_4)), t_3))
else
tmp = r * (2.0d0 * atan2(sqrt((t_4 + (cos(phi1) * (cos(phi2) * (sin((0.5d0 * lambda1)) ** 2.0d0))))), t_3))
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((phi2 * 0.5)) * Math.sin((0.5 * phi1));
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.cos((0.5 * phi1));
double t_3 = Math.sqrt(((1.0 - Math.pow((t_0 - (t_2 * Math.sin((phi2 * 0.5)))), 2.0)) - ((Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1))));
double t_4 = Math.pow((t_0 + (Math.sin((phi2 * -0.5)) * t_2)), 2.0);
double tmp;
if ((lambda2 <= -2.2e-13) || !(lambda2 <= 1.95e-8)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0))) + t_4)), t_3));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_4 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * lambda1)), 2.0))))), t_3));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((phi2 * 0.5)) * math.sin((0.5 * phi1)) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.cos((0.5 * phi1)) t_3 = math.sqrt(((1.0 - math.pow((t_0 - (t_2 * math.sin((phi2 * 0.5)))), 2.0)) - ((math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1)))) t_4 = math.pow((t_0 + (math.sin((phi2 * -0.5)) * t_2)), 2.0) tmp = 0 if (lambda2 <= -2.2e-13) or not (lambda2 <= 1.95e-8): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0))) + t_4)), t_3)) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_4 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * lambda1)), 2.0))))), t_3)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(0.5 * phi1))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = cos(Float64(0.5 * phi1)) t_3 = sqrt(Float64(Float64(1.0 - (Float64(t_0 - Float64(t_2 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)))) t_4 = Float64(t_0 + Float64(sin(Float64(phi2 * -0.5)) * t_2)) ^ 2.0 tmp = 0.0 if ((lambda2 <= -2.2e-13) || !(lambda2 <= 1.95e-8)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0))) + t_4)), t_3))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * lambda1)) ^ 2.0))))), t_3))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((phi2 * 0.5)) * sin((0.5 * phi1)); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = cos((0.5 * phi1)); t_3 = sqrt(((1.0 - ((t_0 - (t_2 * sin((phi2 * 0.5)))) ^ 2.0)) - ((cos(phi1) * cos(phi2)) * (t_1 * t_1)))); t_4 = (t_0 + (sin((phi2 * -0.5)) * t_2)) ^ 2.0; tmp = 0.0; if ((lambda2 <= -2.2e-13) || ~((lambda2 <= 1.95e-8))) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0))) + t_4)), t_3)); else tmp = R * (2.0 * atan2(sqrt((t_4 + (cos(phi1) * (cos(phi2) * (sin((0.5 * lambda1)) ^ 2.0))))), t_3)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[(1.0 - N[Power[N[(t$95$0 - N[(t$95$2 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Power[N[(t$95$0 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[lambda2, -2.2e-13], N[Not[LessEqual[lambda2, 1.95e-8]], $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[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_1\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \left(0.5 \cdot \phi_1\right)\\
t_3 := \sqrt{\left(1 - {\left(t\_0 - t\_2 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) - \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)}\\
t_4 := {\left(t\_0 + \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_2\right)}^{2}\\
\mathbf{if}\;\lambda_2 \leq -2.2 \cdot 10^{-13} \lor \neg \left(\lambda_2 \leq 1.95 \cdot 10^{-8}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}\right) + t\_4}}{t\_3}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right)}}{t\_3}\right)\\
\end{array}
\end{array}
if lambda2 < -2.19999999999999997e-13 or 1.94999999999999992e-8 < lambda2 Initial program 48.9%
associate-*l*48.9%
Simplified48.9%
div-sub48.9%
sin-diff49.7%
div-inv49.7%
metadata-eval49.7%
div-inv49.7%
metadata-eval49.7%
div-inv49.7%
metadata-eval49.7%
div-inv49.7%
metadata-eval49.7%
Applied egg-rr49.7%
div-sub48.9%
sin-diff49.7%
div-inv49.7%
metadata-eval49.7%
div-inv49.7%
metadata-eval49.7%
div-inv49.7%
metadata-eval49.7%
div-inv49.7%
metadata-eval49.7%
Applied egg-rr58.6%
*-commutative58.6%
*-commutative58.6%
fmm-def58.7%
*-commutative58.7%
*-commutative58.7%
*-commutative58.7%
distribute-lft-neg-in58.7%
sin-neg58.7%
distribute-rgt-neg-in58.7%
metadata-eval58.7%
*-commutative58.7%
*-commutative58.7%
Simplified58.7%
Taylor expanded in lambda1 around 0 58.6%
if -2.19999999999999997e-13 < lambda2 < 1.94999999999999992e-8Initial program 79.1%
associate-*l*79.1%
Simplified79.1%
div-sub79.1%
sin-diff80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
Applied egg-rr80.1%
div-sub79.1%
sin-diff80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
Applied egg-rr98.1%
*-commutative98.1%
*-commutative98.1%
fmm-def98.1%
*-commutative98.1%
*-commutative98.1%
*-commutative98.1%
distribute-lft-neg-in98.1%
sin-neg98.1%
distribute-rgt-neg-in98.1%
metadata-eval98.1%
*-commutative98.1%
*-commutative98.1%
Simplified98.1%
Taylor expanded in lambda2 around 0 97.3%
Final simplification76.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_0 (* t_2 t_2)))
(t_4 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_5 (* (cos (* phi2 0.5)) (sin (* 0.5 phi1))))
(t_6 (pow (- t_5 (* t_1 (sin (* phi2 0.5)))) 2.0))
(t_7 (- 1.0 t_6)))
(if (<= lambda1 -6.2e-56)
(* R (* 2.0 (atan2 (sqrt (+ t_3 t_6)) (sqrt (- (- 1.0 t_4) t_3)))))
(if (<= lambda1 0.00145)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0)))
(pow (+ t_5 (* (sin (* phi2 -0.5)) t_1)) 2.0)))
(sqrt (- t_7 t_3)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_3 t_4))
(sqrt (- t_7 (* t_0 (pow (sin (* 0.5 lambda1)) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = cos((0.5 * phi1));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_0 * (t_2 * t_2);
double t_4 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_5 = cos((phi2 * 0.5)) * sin((0.5 * phi1));
double t_6 = pow((t_5 - (t_1 * sin((phi2 * 0.5)))), 2.0);
double t_7 = 1.0 - t_6;
double tmp;
if (lambda1 <= -6.2e-56) {
tmp = R * (2.0 * atan2(sqrt((t_3 + t_6)), sqrt(((1.0 - t_4) - t_3))));
} else if (lambda1 <= 0.00145) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0))) + pow((t_5 + (sin((phi2 * -0.5)) * t_1)), 2.0))), sqrt((t_7 - t_3))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_3 + t_4)), sqrt((t_7 - (t_0 * pow(sin((0.5 * lambda1)), 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) :: t_3
real(8) :: t_4
real(8) :: t_5
real(8) :: t_6
real(8) :: t_7
real(8) :: tmp
t_0 = cos(phi1) * cos(phi2)
t_1 = cos((0.5d0 * phi1))
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = t_0 * (t_2 * t_2)
t_4 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_5 = cos((phi2 * 0.5d0)) * sin((0.5d0 * phi1))
t_6 = (t_5 - (t_1 * sin((phi2 * 0.5d0)))) ** 2.0d0
t_7 = 1.0d0 - t_6
if (lambda1 <= (-6.2d-56)) then
tmp = r * (2.0d0 * atan2(sqrt((t_3 + t_6)), sqrt(((1.0d0 - t_4) - t_3))))
else if (lambda1 <= 0.00145d0) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 2.0d0))) + ((t_5 + (sin((phi2 * (-0.5d0))) * t_1)) ** 2.0d0))), sqrt((t_7 - t_3))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_3 + t_4)), sqrt((t_7 - (t_0 * (sin((0.5d0 * lambda1)) ** 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.cos(phi1) * Math.cos(phi2);
double t_1 = Math.cos((0.5 * phi1));
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_0 * (t_2 * t_2);
double t_4 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_5 = Math.cos((phi2 * 0.5)) * Math.sin((0.5 * phi1));
double t_6 = Math.pow((t_5 - (t_1 * Math.sin((phi2 * 0.5)))), 2.0);
double t_7 = 1.0 - t_6;
double tmp;
if (lambda1 <= -6.2e-56) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + t_6)), Math.sqrt(((1.0 - t_4) - t_3))));
} else if (lambda1 <= 0.00145) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0))) + Math.pow((t_5 + (Math.sin((phi2 * -0.5)) * t_1)), 2.0))), Math.sqrt((t_7 - t_3))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + t_4)), Math.sqrt((t_7 - (t_0 * Math.pow(Math.sin((0.5 * lambda1)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.cos((0.5 * phi1)) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = t_0 * (t_2 * t_2) t_4 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_5 = math.cos((phi2 * 0.5)) * math.sin((0.5 * phi1)) t_6 = math.pow((t_5 - (t_1 * math.sin((phi2 * 0.5)))), 2.0) t_7 = 1.0 - t_6 tmp = 0 if lambda1 <= -6.2e-56: tmp = R * (2.0 * math.atan2(math.sqrt((t_3 + t_6)), math.sqrt(((1.0 - t_4) - t_3)))) elif lambda1 <= 0.00145: tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0))) + math.pow((t_5 + (math.sin((phi2 * -0.5)) * t_1)), 2.0))), math.sqrt((t_7 - t_3)))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_3 + t_4)), math.sqrt((t_7 - (t_0 * math.pow(math.sin((0.5 * lambda1)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = cos(Float64(0.5 * phi1)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_0 * Float64(t_2 * t_2)) t_4 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_5 = Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(0.5 * phi1))) t_6 = Float64(t_5 - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_7 = Float64(1.0 - t_6) tmp = 0.0 if (lambda1 <= -6.2e-56) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + t_6)), sqrt(Float64(Float64(1.0 - t_4) - t_3))))); elseif (lambda1 <= 0.00145) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0))) + (Float64(t_5 + Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0))), sqrt(Float64(t_7 - t_3))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + t_4)), sqrt(Float64(t_7 - Float64(t_0 * (sin(Float64(0.5 * lambda1)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = cos((0.5 * phi1)); t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = t_0 * (t_2 * t_2); t_4 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_5 = cos((phi2 * 0.5)) * sin((0.5 * phi1)); t_6 = (t_5 - (t_1 * sin((phi2 * 0.5)))) ^ 2.0; t_7 = 1.0 - t_6; tmp = 0.0; if (lambda1 <= -6.2e-56) tmp = R * (2.0 * atan2(sqrt((t_3 + t_6)), sqrt(((1.0 - t_4) - t_3)))); elseif (lambda1 <= 0.00145) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0))) + ((t_5 + (sin((phi2 * -0.5)) * t_1)) ^ 2.0))), sqrt((t_7 - t_3)))); else tmp = R * (2.0 * atan2(sqrt((t_3 + t_4)), sqrt((t_7 - (t_0 * (sin((0.5 * lambda1)) ^ 2.0)))))); 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[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$5 = N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[Power[N[(t$95$5 - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$7 = N[(1.0 - t$95$6), $MachinePrecision]}, If[LessEqual[lambda1, -6.2e-56], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + t$95$6), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$4), $MachinePrecision] - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 0.00145], 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[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$5 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$7 - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$7 - N[(t$95$0 * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_0 \cdot \left(t\_2 \cdot t\_2\right)\\
t_4 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_5 := \cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_1\right)\\
t_6 := {\left(t\_5 - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_7 := 1 - t\_6\\
\mathbf{if}\;\lambda_1 \leq -6.2 \cdot 10^{-56}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + t\_6}}{\sqrt{\left(1 - t\_4\right) - t\_3}}\right)\\
\mathbf{elif}\;\lambda_1 \leq 0.00145:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}\right) + {\left(t\_5 + \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_1\right)}^{2}}}{\sqrt{t\_7 - t\_3}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + t\_4}}{\sqrt{t\_7 - t\_0 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)\\
\end{array}
\end{array}
if lambda1 < -6.19999999999999975e-56Initial program 52.7%
associate-*l*52.7%
Simplified52.7%
div-sub52.7%
sin-diff53.1%
div-inv53.1%
metadata-eval53.1%
div-inv53.1%
metadata-eval53.1%
div-inv53.1%
metadata-eval53.1%
div-inv53.1%
metadata-eval53.1%
Applied egg-rr53.3%
if -6.19999999999999975e-56 < lambda1 < 0.00145Initial program 78.9%
associate-*l*78.9%
Simplified78.9%
div-sub78.9%
sin-diff80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
Applied egg-rr80.1%
div-sub78.9%
sin-diff80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
Applied egg-rr97.6%
*-commutative97.6%
*-commutative97.6%
fmm-def97.6%
*-commutative97.6%
*-commutative97.6%
*-commutative97.6%
distribute-lft-neg-in97.6%
sin-neg97.6%
distribute-rgt-neg-in97.6%
metadata-eval97.6%
*-commutative97.6%
*-commutative97.6%
Simplified97.6%
Taylor expanded in lambda1 around 0 97.6%
if 0.00145 < lambda1 Initial program 44.3%
associate-*l*44.3%
Simplified44.3%
div-sub44.3%
sin-diff45.4%
div-inv45.4%
metadata-eval45.4%
div-inv45.4%
metadata-eval45.4%
div-inv45.4%
metadata-eval45.4%
div-inv45.4%
metadata-eval45.4%
Applied egg-rr45.4%
Taylor expanded in lambda2 around 0 45.6%
Final simplification72.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(pow
(-
(* (cos (* phi2 0.5)) (sin (* 0.5 phi1)))
(* (cos (* 0.5 phi1)) (sin (* phi2 0.5))))
2.0))
(t_2 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(* R (* 2.0 (atan2 (sqrt (+ t_2 t_1)) (sqrt (- (- 1.0 t_1) t_2)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(((cos((phi2 * 0.5)) * sin((0.5 * phi1))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))), 2.0);
double t_2 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_2 + t_1)), sqrt(((1.0 - t_1) - 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(((lambda1 - lambda2) / 2.0d0))
t_1 = ((cos((phi2 * 0.5d0)) * sin((0.5d0 * phi1))) - (cos((0.5d0 * phi1)) * sin((phi2 * 0.5d0)))) ** 2.0d0
t_2 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_2 + t_1)), sqrt(((1.0d0 - t_1) - t_2))))
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.cos((phi2 * 0.5)) * Math.sin((0.5 * phi1))) - (Math.cos((0.5 * phi1)) * Math.sin((phi2 * 0.5)))), 2.0);
double t_2 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_2 + t_1)), Math.sqrt(((1.0 - t_1) - t_2))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(((math.cos((phi2 * 0.5)) * math.sin((0.5 * phi1))) - (math.cos((0.5 * phi1)) * math.sin((phi2 * 0.5)))), 2.0) t_2 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_2 + t_1)), math.sqrt(((1.0 - t_1) - t_2))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(0.5 * phi1))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_2 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + t_1)), sqrt(Float64(Float64(1.0 - t_1) - t_2))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = ((cos((phi2 * 0.5)) * sin((0.5 * phi1))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))) ^ 2.0; t_2 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_2 + t_1)), sqrt(((1.0 - t_1) - t_2)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = 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$2 + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] - t$95$2), $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 \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_1\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_2 := \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\_2 + t\_1}}{\sqrt{\left(1 - t\_1\right) - t\_2}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified63.0%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr77.0%
Final simplification77.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 phi1)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (cos (* phi2 0.5)))
(t_4 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma t_3 t_0 (* (sin (* phi2 -0.5)) t_1)) 2.0)
(* t_2 (* t_4 t_4))))
(sqrt
(+
(- 1.0 (pow (- (* t_3 t_0) (* t_1 (sin (* phi2 0.5)))) 2.0))
(* t_2 (/ 1.0 (/ 2.0 (+ (cos (- lambda1 lambda2)) -1.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * phi1));
double t_1 = cos((0.5 * phi1));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = cos((phi2 * 0.5));
double t_4 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(t_3, t_0, (sin((phi2 * -0.5)) * t_1)), 2.0) + (t_2 * (t_4 * t_4)))), sqrt(((1.0 - pow(((t_3 * t_0) - (t_1 * sin((phi2 * 0.5)))), 2.0)) + (t_2 * (1.0 / (2.0 / (cos((lambda1 - lambda2)) + -1.0))))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi1)) t_1 = cos(Float64(0.5 * phi1)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = cos(Float64(phi2 * 0.5)) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_3, t_0, Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0) + Float64(t_2 * Float64(t_4 * t_4)))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_3 * t_0) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) + Float64(t_2 * Float64(1.0 / Float64(2.0 / Float64(cos(Float64(lambda1 - lambda2)) + -1.0))))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$3 * t$95$0 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$3 * t$95$0), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(1.0 / N[(2.0 / N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \phi_1\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \cos \left(\phi_2 \cdot 0.5\right)\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_3, t\_0, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_1\right)\right)}^{2} + t\_2 \cdot \left(t\_4 \cdot t\_4\right)}}{\sqrt{\left(1 - {\left(t\_3 \cdot t\_0 - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) + t\_2 \cdot \frac{1}{\frac{2}{\cos \left(\lambda_1 - \lambda_2\right) + -1}}}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified63.0%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr77.0%
*-commutative77.0%
*-commutative77.0%
fmm-def77.0%
*-commutative77.0%
*-commutative77.0%
*-commutative77.0%
distribute-lft-neg-in77.0%
sin-neg77.0%
distribute-rgt-neg-in77.0%
metadata-eval77.0%
*-commutative77.0%
*-commutative77.0%
Simplified77.0%
sin-mult77.0%
clear-num77.0%
+-inverses77.0%
add-log-exp28.2%
add-log-exp28.2%
sum-log28.2%
exp-sqrt28.2%
exp-sqrt28.2%
add-sqr-sqrt28.2%
add-log-exp77.0%
Applied egg-rr77.0%
Final simplification77.0%
(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
(-
(* (cos (* phi2 0.5)) (sin (* 0.5 phi1)))
(* (cos (* 0.5 phi1)) (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((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(((cos((phi2 * 0.5)) * sin((0.5 * phi1))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (((cos((phi2 * 0.5d0)) * sin((0.5d0 * phi1))) - (cos((0.5d0 * phi1)) * sin((phi2 * 0.5d0)))) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((0.5 * phi1))) - (Math.cos((0.5 * phi1)) * Math.sin((phi2 * 0.5)))), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - math.pow(((math.cos((phi2 * 0.5)) * math.sin((0.5 * phi1))) - (math.cos((0.5 * phi1)) * math.sin((phi2 * 0.5)))), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(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(cos(Float64(phi2 * 0.5)) * sin(Float64(0.5 * phi1))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(phi2 * 0.5)))) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (((cos((phi2 * 0.5)) * sin((0.5 * phi1))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[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[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $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{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_1\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified63.0%
div-sub63.0%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
Final simplification63.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(fabs
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(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));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(fabs((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), pow(sin((-0.5 * (phi2 - phi1))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(abs(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), (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]}, 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[Abs[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 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)\\
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{\left|1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified63.0%
Applied egg-rr63.3%
unpow1/263.3%
unpow263.3%
rem-sqrt-square63.3%
metadata-eval63.3%
cancel-sign-sub-inv63.3%
*-commutative63.3%
Simplified63.3%
Final simplification63.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (* (cos phi2) t_1))
(t_3 (* (* (cos phi1) (cos phi2)) (* t_0 t_0)))
(t_4 (pow (cos (* phi2 0.5)) 2.0))
(t_5 (sqrt (+ t_3 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
(if (<= phi2 -52000000.0)
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- t_4 t_3)))))
(if (<= phi2 3.3)
(*
R
(*
2.0
(atan2
t_5
(sqrt (- 1.0 (+ (* (cos phi1) t_1) (pow (sin (* 0.5 phi1)) 2.0)))))))
(* R (* 2.0 (atan2 t_5 (sqrt (- t_4 t_2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = cos(phi2) * t_1;
double t_3 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
double t_4 = pow(cos((phi2 * 0.5)), 2.0);
double t_5 = sqrt((t_3 + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if (phi2 <= -52000000.0) {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin((phi2 * -0.5)), 2.0))), sqrt((t_4 - t_3))));
} else if (phi2 <= 3.3) {
tmp = R * (2.0 * atan2(t_5, sqrt((1.0 - ((cos(phi1) * t_1) + pow(sin((0.5 * phi1)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_5, sqrt((t_4 - t_2))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: t_5
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_2 = cos(phi2) * t_1
t_3 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
t_4 = cos((phi2 * 0.5d0)) ** 2.0d0
t_5 = sqrt((t_3 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)))
if (phi2 <= (-52000000.0d0)) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt((t_4 - t_3))))
else if (phi2 <= 3.3d0) then
tmp = r * (2.0d0 * atan2(t_5, sqrt((1.0d0 - ((cos(phi1) * t_1) + (sin((0.5d0 * phi1)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(t_5, sqrt((t_4 - t_2))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = Math.cos(phi2) * t_1;
double t_3 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
double t_4 = Math.pow(Math.cos((phi2 * 0.5)), 2.0);
double t_5 = Math.sqrt((t_3 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if (phi2 <= -52000000.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((t_4 - t_3))));
} else if (phi2 <= 3.3) {
tmp = R * (2.0 * Math.atan2(t_5, Math.sqrt((1.0 - ((Math.cos(phi1) * t_1) + Math.pow(Math.sin((0.5 * phi1)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(t_5, Math.sqrt((t_4 - t_2))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_2 = math.cos(phi2) * t_1 t_3 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) t_4 = math.pow(math.cos((phi2 * 0.5)), 2.0) t_5 = math.sqrt((t_3 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))) tmp = 0 if phi2 <= -52000000.0: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((t_4 - t_3)))) elif phi2 <= 3.3: tmp = R * (2.0 * math.atan2(t_5, math.sqrt((1.0 - ((math.cos(phi1) * t_1) + math.pow(math.sin((0.5 * phi1)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(t_5, math.sqrt((t_4 - t_2)))) 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(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(cos(phi2) * t_1) t_3 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) t_4 = cos(Float64(phi2 * 0.5)) ^ 2.0 t_5 = sqrt(Float64(t_3 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) tmp = 0.0 if (phi2 <= -52000000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(t_4 - t_3))))); elseif (phi2 <= 3.3) tmp = Float64(R * Float64(2.0 * atan(t_5, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_1) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_5, sqrt(Float64(t_4 - t_2))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_2 = cos(phi2) * t_1; t_3 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); t_4 = cos((phi2 * 0.5)) ^ 2.0; t_5 = sqrt((t_3 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))); tmp = 0.0; if (phi2 <= -52000000.0) tmp = R * (2.0 * atan2(sqrt((t_2 + (sin((phi2 * -0.5)) ^ 2.0))), sqrt((t_4 - t_3)))); elseif (phi2 <= 3.3) tmp = R * (2.0 * atan2(t_5, sqrt((1.0 - ((cos(phi1) * t_1) + (sin((0.5 * phi1)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(t_5, sqrt((t_4 - t_2)))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Power[N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$5 = N[Sqrt[N[(t$95$3 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -52000000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$4 - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 3.3], N[(R * N[(2.0 * N[ArcTan[t$95$5 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$5 / N[Sqrt[N[(t$95$4 - t$95$2), $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(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \cos \phi_2 \cdot t\_1\\
t_3 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
t_4 := {\cos \left(\phi_2 \cdot 0.5\right)}^{2}\\
t_5 := \sqrt{t\_3 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
\mathbf{if}\;\phi_2 \leq -52000000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{t\_4 - t\_3}}\right)\\
\mathbf{elif}\;\phi_2 \leq 3.3:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_5}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_1 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_5}{\sqrt{t\_4 - t\_2}}\right)\\
\end{array}
\end{array}
if phi2 < -5.2e7Initial program 54.0%
associate-*l*54.0%
Simplified54.0%
Taylor expanded in phi1 around 0 54.0%
unpow254.0%
1-sub-sin54.2%
unpow254.2%
*-commutative54.2%
metadata-eval54.2%
distribute-rgt-neg-in54.2%
cos-neg54.2%
Simplified54.2%
Taylor expanded in phi1 around 0 55.3%
if -5.2e7 < phi2 < 3.2999999999999998Initial program 73.1%
associate-*l*73.1%
Simplified73.2%
Taylor expanded in phi2 around 0 73.3%
if 3.2999999999999998 < phi2 Initial program 50.3%
associate-*l*50.2%
Simplified50.2%
Taylor expanded in phi1 around 0 50.2%
unpow250.2%
1-sub-sin50.3%
unpow250.3%
*-commutative50.3%
metadata-eval50.3%
distribute-rgt-neg-in50.3%
cos-neg50.3%
Simplified50.3%
Taylor expanded in phi1 around 0 51.4%
*-commutative51.4%
Simplified51.4%
Final simplification63.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (+ 1.0 (- (/ (cos (- phi1 phi2)) 2.0) 0.5)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - 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 + ((cos((phi1 - phi2)) / 2.0d0) - 0.5d0)) - 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.cos((phi1 - phi2)) / 2.0) - 0.5)) - 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.cos((phi1 - phi2)) / 2.0) - 0.5)) - 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(cos(Float64(phi1 - phi2)) / 2.0) - 0.5)) - 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 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[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[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $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(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right)\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified63.0%
unpow263.0%
sin-mult63.0%
div-inv63.0%
metadata-eval63.0%
div-inv63.0%
metadata-eval63.0%
div-inv63.0%
metadata-eval63.0%
div-inv63.0%
metadata-eval63.0%
Applied egg-rr63.0%
div-sub63.0%
+-inverses63.0%
cos-063.0%
metadata-eval63.0%
distribute-lft-out63.0%
metadata-eval63.0%
*-rgt-identity63.0%
Simplified63.0%
Final simplification63.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(if (or (<= phi2 -52000000.0) (not (<= phi2 4e-14)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) t_1) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 0.5)) 2.0) t_2)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt
(- 1.0 (+ (* (cos phi1) t_1) (pow (sin (* 0.5 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 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
double tmp;
if ((phi2 <= -52000000.0) || !(phi2 <= 4e-14)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_1) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * 0.5)), 2.0) - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin((phi1 / 2.0)), 2.0))), sqrt((1.0 - ((cos(phi1) * t_1) + pow(sin((0.5 * phi1)), 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 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_2 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
if ((phi2 <= (-52000000.0d0)) .or. (.not. (phi2 <= 4d-14))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * t_1) + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt(((cos((phi2 * 0.5d0)) ** 2.0d0) - t_2))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin((phi1 / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - ((cos(phi1) * t_1) + (sin((0.5d0 * phi1)) ** 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.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
double tmp;
if ((phi2 <= -52000000.0) || !(phi2 <= 4e-14)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * t_1) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * 0.5)), 2.0) - t_2))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin((phi1 / 2.0)), 2.0))), Math.sqrt((1.0 - ((Math.cos(phi1) * t_1) + Math.pow(Math.sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_2 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) tmp = 0 if (phi2 <= -52000000.0) or not (phi2 <= 4e-14): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * t_1) + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi2 * 0.5)), 2.0) - t_2)))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin((phi1 / 2.0)), 2.0))), math.sqrt((1.0 - ((math.cos(phi1) * t_1) + math.pow(math.sin((0.5 * phi1)), 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(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) tmp = 0.0 if ((phi2 <= -52000000.0) || !(phi2 <= 4e-14)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * t_1) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * 0.5)) ^ 2.0) - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_1) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_2 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = 0.0; if ((phi2 <= -52000000.0) || ~((phi2 <= 4e-14))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_1) + (sin((phi2 * -0.5)) ^ 2.0))), sqrt(((cos((phi2 * 0.5)) ^ 2.0) - t_2)))); else tmp = R * (2.0 * atan2(sqrt((t_2 + (sin((phi1 / 2.0)) ^ 2.0))), sqrt((1.0 - ((cos(phi1) * t_1) + (sin((0.5 * phi1)) ^ 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[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -52000000.0], N[Not[LessEqual[phi2, 4e-14]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -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] - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $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(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
\mathbf{if}\;\phi_2 \leq -52000000 \lor \neg \left(\phi_2 \leq 4 \cdot 10^{-14}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_1 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot 0.5\right)}^{2} - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_1 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -5.2e7 or 4e-14 < phi2 Initial program 53.0%
associate-*l*53.0%
Simplified53.0%
Taylor expanded in phi1 around 0 52.8%
unpow252.8%
1-sub-sin52.9%
unpow252.9%
*-commutative52.9%
metadata-eval52.9%
distribute-rgt-neg-in52.9%
cos-neg52.9%
Simplified52.9%
Taylor expanded in phi1 around 0 53.7%
if -5.2e7 < phi2 < 4e-14Initial program 72.9%
associate-*l*72.9%
Simplified73.0%
div-sub73.0%
sin-diff73.2%
div-inv73.2%
metadata-eval73.2%
div-inv73.2%
metadata-eval73.2%
div-inv73.2%
metadata-eval73.2%
div-inv73.2%
metadata-eval73.2%
Applied egg-rr73.2%
Taylor expanded in phi1 around inf 72.4%
Taylor expanded in phi2 around 0 72.3%
Final simplification63.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (cos (* phi2 0.5)) 2.0))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_3 (* (cos phi2) t_2))
(t_4 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(if (<= phi2 -52000000.0)
(*
R
(*
2.0
(atan2
(sqrt (+ t_3 (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- t_1 t_4)))))
(if (<= phi2 2e-13)
(*
R
(*
2.0
(atan2
(sqrt (+ t_4 (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt (- 1.0 (+ (* (cos phi1) t_2) (pow (sin (* 0.5 phi1)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_4 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- t_1 t_3)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(cos((phi2 * 0.5)), 2.0);
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_3 = cos(phi2) * t_2;
double t_4 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
double tmp;
if (phi2 <= -52000000.0) {
tmp = R * (2.0 * atan2(sqrt((t_3 + pow(sin((phi2 * -0.5)), 2.0))), sqrt((t_1 - t_4))));
} else if (phi2 <= 2e-13) {
tmp = R * (2.0 * atan2(sqrt((t_4 + pow(sin((phi1 / 2.0)), 2.0))), sqrt((1.0 - ((cos(phi1) * t_2) + pow(sin((0.5 * phi1)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_4 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((t_1 - t_3))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos((phi2 * 0.5d0)) ** 2.0d0
t_2 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_3 = cos(phi2) * t_2
t_4 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
if (phi2 <= (-52000000.0d0)) then
tmp = r * (2.0d0 * atan2(sqrt((t_3 + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt((t_1 - t_4))))
else if (phi2 <= 2d-13) then
tmp = r * (2.0d0 * atan2(sqrt((t_4 + (sin((phi1 / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - ((cos(phi1) * t_2) + (sin((0.5d0 * phi1)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_4 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((t_1 - t_3))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.cos((phi2 * 0.5)), 2.0);
double t_2 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_3 = Math.cos(phi2) * t_2;
double t_4 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
double tmp;
if (phi2 <= -52000000.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((t_1 - t_4))));
} else if (phi2 <= 2e-13) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_4 + Math.pow(Math.sin((phi1 / 2.0)), 2.0))), Math.sqrt((1.0 - ((Math.cos(phi1) * t_2) + Math.pow(Math.sin((0.5 * phi1)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_4 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((t_1 - t_3))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.cos((phi2 * 0.5)), 2.0) t_2 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_3 = math.cos(phi2) * t_2 t_4 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) tmp = 0 if phi2 <= -52000000.0: tmp = R * (2.0 * math.atan2(math.sqrt((t_3 + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((t_1 - t_4)))) elif phi2 <= 2e-13: tmp = R * (2.0 * math.atan2(math.sqrt((t_4 + math.pow(math.sin((phi1 / 2.0)), 2.0))), math.sqrt((1.0 - ((math.cos(phi1) * t_2) + math.pow(math.sin((0.5 * phi1)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_4 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((t_1 - t_3)))) 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)) ^ 2.0 t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_3 = Float64(cos(phi2) * t_2) t_4 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) tmp = 0.0 if (phi2 <= -52000000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(t_1 - t_4))))); elseif (phi2 <= 2e-13) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_2) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(t_1 - t_3))))); 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)) ^ 2.0; t_2 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_3 = cos(phi2) * t_2; t_4 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = 0.0; if (phi2 <= -52000000.0) tmp = R * (2.0 * atan2(sqrt((t_3 + (sin((phi2 * -0.5)) ^ 2.0))), sqrt((t_1 - t_4)))); elseif (phi2 <= 2e-13) tmp = R * (2.0 * atan2(sqrt((t_4 + (sin((phi1 / 2.0)) ^ 2.0))), sqrt((1.0 - ((cos(phi1) * t_2) + (sin((0.5 * phi1)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((t_4 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((t_1 - t_3)))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision]}, Block[{t$95$4 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, -52000000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$1 - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2e-13], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$1 - t$95$3), $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)}^{2}\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_3 := \cos \phi_2 \cdot t\_2\\
t_4 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
\mathbf{if}\;\phi_2 \leq -52000000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{t\_1 - t\_4}}\right)\\
\mathbf{elif}\;\phi_2 \leq 2 \cdot 10^{-13}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_2 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{t\_1 - t\_3}}\right)\\
\end{array}
\end{array}
if phi2 < -5.2e7Initial program 54.0%
associate-*l*54.0%
Simplified54.0%
Taylor expanded in phi1 around 0 54.0%
unpow254.0%
1-sub-sin54.2%
unpow254.2%
*-commutative54.2%
metadata-eval54.2%
distribute-rgt-neg-in54.2%
cos-neg54.2%
Simplified54.2%
Taylor expanded in phi1 around 0 55.3%
if -5.2e7 < phi2 < 2.0000000000000001e-13Initial program 72.9%
associate-*l*72.9%
Simplified73.0%
div-sub73.0%
sin-diff73.2%
div-inv73.2%
metadata-eval73.2%
div-inv73.2%
metadata-eval73.2%
div-inv73.2%
metadata-eval73.2%
div-inv73.2%
metadata-eval73.2%
Applied egg-rr73.2%
Taylor expanded in phi1 around inf 72.4%
Taylor expanded in phi2 around 0 72.3%
if 2.0000000000000001e-13 < phi2 Initial program 52.0%
associate-*l*52.0%
Simplified52.0%
Taylor expanded in phi1 around 0 51.7%
unpow251.7%
1-sub-sin51.7%
unpow251.7%
*-commutative51.7%
metadata-eval51.7%
distribute-rgt-neg-in51.7%
cos-neg51.7%
Simplified51.7%
Taylor expanded in phi1 around 0 53.1%
*-commutative53.1%
Simplified53.1%
Final simplification63.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (sin (* 0.5 (- lambda1 lambda2))))
(t_3 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -3.2e-32) (not (<= phi2 3.3)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) (pow t_2 2.0)) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 0.5)) 2.0) (* t_3 (* t_1 t_1)))))))
(*
(* R 2.0)
(atan2
(hypot t_0 (* (sqrt t_3) t_2))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ (+ 1.5 (* -0.5 (cos (- lambda2 lambda1)))) -1.0))
(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)));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sin((0.5 * (lambda1 - lambda2)));
double t_3 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -3.2e-32) || !(phi2 <= 3.3)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(t_2, 2.0)) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * 0.5)), 2.0) - (t_3 * (t_1 * t_1))))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_0, (sqrt(t_3) * t_2)), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * ((1.5 + (-0.5 * cos((lambda2 - lambda1)))) + -1.0)), pow(t_0, 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_3 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -3.2e-32) || !(phi2 <= 3.3)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (t_2 ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * 0.5)) ^ 2.0) - Float64(t_3 * Float64(t_1 * t_1))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(sqrt(t_3) * t_2)), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(Float64(1.5 + Float64(-0.5 * cos(Float64(lambda2 - lambda1)))) + -1.0)), (t_0 ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -3.2e-32], N[Not[LessEqual[phi2, 3.3]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -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[(t$95$3 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(N[Sqrt[t$95$3], $MachinePrecision] * t$95$2), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(N[(1.5 + N[(-0.5 * N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $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)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -3.2 \cdot 10^{-32} \lor \neg \left(\phi_2 \leq 3.3\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {t\_2}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot 0.5\right)}^{2} - t\_3 \cdot \left(t\_1 \cdot t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, \sqrt{t\_3} \cdot t\_2\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(\left(1.5 + -0.5 \cdot \cos \left(\lambda_2 - \lambda_1\right)\right) + -1\right), {t\_0}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -3.2000000000000002e-32 or 3.2999999999999998 < phi2 Initial program 52.1%
associate-*l*52.1%
Simplified52.1%
Taylor expanded in phi1 around 0 50.8%
unpow250.8%
1-sub-sin50.9%
unpow250.9%
*-commutative50.9%
metadata-eval50.9%
distribute-rgt-neg-in50.9%
cos-neg50.9%
Simplified50.9%
Taylor expanded in phi1 around 0 51.6%
if -3.2000000000000002e-32 < phi2 < 3.2999999999999998Initial program 74.3%
associate-*r*74.3%
*-commutative74.3%
Simplified74.3%
Applied egg-rr56.5%
*-lft-identity56.5%
*-commutative56.5%
*-commutative56.5%
metadata-eval56.5%
cancel-sign-sub-inv56.5%
Simplified56.5%
expm1-log1p-u56.4%
cancel-sign-sub-inv56.4%
metadata-eval56.4%
Applied egg-rr56.4%
expm1-undefine56.5%
sub-neg56.5%
log1p-undefine56.5%
rem-exp-log56.5%
associate-+r+56.5%
metadata-eval56.5%
sub-neg56.5%
remove-double-neg56.5%
mul-1-neg56.5%
distribute-neg-in56.5%
+-commutative56.5%
cos-neg56.5%
mul-1-neg56.5%
unsub-neg56.5%
metadata-eval56.5%
Simplified56.5%
Final simplification54.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (sin (* 0.5 (- lambda1 lambda2))))
(t_2 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -2.6e-34) (not (<= phi2 3.3)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) (pow t_1 2.0)) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 0.5)) 2.0) (* t_2 (* t_0 t_0)))))))
(*
(* R 2.0)
(atan2
(hypot (sin (* 0.5 (- phi1 phi2))) (* (sqrt t_2) t_1))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 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 = sin((0.5 * (lambda1 - lambda2)));
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -2.6e-34) || !(phi2 <= 3.3)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(t_1, 2.0)) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * 0.5)), 2.0) - (t_2 * (t_0 * t_0))))));
} else {
tmp = (R * 2.0) * atan2(hypot(sin((0.5 * (phi1 - phi2))), (sqrt(t_2) * t_1)), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * phi1)), 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(lambda1 - lambda2))) t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -2.6e-34) || !(phi2 <= 3.3)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (t_1 ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * 0.5)) ^ 2.0) - Float64(t_2 * Float64(t_0 * t_0))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(sqrt(t_2) * t_1)), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * phi1)) ^ 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -2.6e-34], N[Not[LessEqual[phi2, 3.3]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -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[(t$95$2 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(N[Sqrt[t$95$2], $MachinePrecision] * t$95$1), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $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(\lambda_1 - \lambda_2\right)\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -2.6 \cdot 10^{-34} \lor \neg \left(\phi_2 \leq 3.3\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {t\_1}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot 0.5\right)}^{2} - t\_2 \cdot \left(t\_0 \cdot t\_0\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), \sqrt{t\_2} \cdot t\_1\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -2.5999999999999999e-34 or 3.2999999999999998 < phi2 Initial program 52.1%
associate-*l*52.1%
Simplified52.1%
Taylor expanded in phi1 around 0 50.8%
unpow250.8%
1-sub-sin50.9%
unpow250.9%
*-commutative50.9%
metadata-eval50.9%
distribute-rgt-neg-in50.9%
cos-neg50.9%
Simplified50.9%
Taylor expanded in phi1 around 0 51.6%
if -2.5999999999999999e-34 < phi2 < 3.2999999999999998Initial program 74.3%
associate-*r*74.3%
*-commutative74.3%
Simplified74.3%
Applied egg-rr56.5%
*-lft-identity56.5%
*-commutative56.5%
*-commutative56.5%
metadata-eval56.5%
cancel-sign-sub-inv56.5%
Simplified56.5%
Taylor expanded in phi2 around 0 56.5%
Final simplification54.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi2 -0.5)) 2.0))
(t_1 (sin (* 0.5 (- lambda1 lambda2))))
(t_2 (sin (* 0.5 (- phi1 phi2)))))
(if (or (<= phi2 -1.02e+52) (not (<= phi2 52000.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (cos phi2) (* t_1 (fabs t_1)))))
(sqrt (- 1.0 (+ (* (cos phi2) (pow t_1 2.0)) t_0))))))
(*
(* R 2.0)
(atan2
(hypot t_2 (* (sqrt (* (cos phi1) (cos phi2))) t_1))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(pow t_2 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi2 * -0.5)), 2.0);
double t_1 = sin((0.5 * (lambda1 - lambda2)));
double t_2 = sin((0.5 * (phi1 - phi2)));
double tmp;
if ((phi2 <= -1.02e+52) || !(phi2 <= 52000.0)) {
tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi2) * (t_1 * fabs(t_1))))), sqrt((1.0 - ((cos(phi2) * pow(t_1, 2.0)) + t_0)))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_2, (sqrt((cos(phi1) * cos(phi2))) * t_1)), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), pow(t_2, 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi2 * -0.5)) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_2 = sin(Float64(0.5 * Float64(phi1 - phi2))) tmp = 0.0 if ((phi2 <= -1.02e+52) || !(phi2 <= 52000.0)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(cos(phi2) * Float64(t_1 * abs(t_1))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (t_1 ^ 2.0)) + t_0)))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_2, Float64(sqrt(Float64(cos(phi1) * cos(phi2))) * t_1)), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), (t_2 ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -1.02e+52], N[Not[LessEqual[phi2, 52000.0]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi2], $MachinePrecision] * N[(t$95$1 * N[Abs[t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$2 ^ 2 + N[(N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
t_1 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_2 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
\mathbf{if}\;\phi_2 \leq -1.02 \cdot 10^{+52} \lor \neg \left(\phi_2 \leq 52000\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_2 \cdot \left(t\_1 \cdot \left|t\_1\right|\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot {t\_1}^{2} + t\_0\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_2, \sqrt{\cos \phi_1 \cdot \cos \phi_2} \cdot t\_1\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {t\_2}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -1.02000000000000002e52 or 52000 < phi2 Initial program 51.3%
add-sqr-sqrt25.0%
sqrt-prod44.2%
rem-sqrt-square44.2%
div-inv44.2%
metadata-eval44.2%
Applied egg-rr44.2%
Taylor expanded in phi1 around 0 44.3%
Taylor expanded in phi1 around 0 44.1%
Taylor expanded in phi1 around 0 44.6%
if -1.02000000000000002e52 < phi2 < 52000Initial program 72.5%
associate-*r*72.5%
*-commutative72.5%
Simplified72.5%
Applied egg-rr54.4%
*-lft-identity54.4%
*-commutative54.4%
*-commutative54.4%
metadata-eval54.4%
cancel-sign-sub-inv54.4%
Simplified54.4%
Final simplification50.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_2 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_2 (* t_0 t_0)) t_1))
(sqrt
(+ (- 1.0 t_1) (* t_2 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
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(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_2 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0d0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0))))))
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);
double t_2 = Math.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt(((t_2 * (t_0 * t_0)) + t_1)), Math.sqrt(((1.0 - t_1) + (t_2 * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
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) t_2 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt(((t_2 * (t_0 * t_0)) + t_1)), math.sqrt(((1.0 - t_1) + (t_2 * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_2 * Float64(t_0 * t_0)) + t_1)), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_2 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) 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; t_2 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$2 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $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(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 \cdot \left(t\_0 \cdot t\_0\right) + t\_1}}{\sqrt{\left(1 - t\_1\right) + t\_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified63.0%
sin-mult74.6%
cos-sum74.5%
cos-274.6%
div-sub74.6%
+-inverses74.6%
Applied egg-rr63.0%
cos-074.6%
metadata-eval74.6%
Simplified63.0%
Final simplification63.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (sin (* 0.5 (- lambda1 lambda2))))
(t_2 (pow t_0 2.0)))
(if (or (<= lambda2 -3.4e-25) (not (<= lambda2 2.75e-8)))
(*
(* R 2.0)
(atan2
(hypot (sin (* 0.5 phi1)) (* t_1 (sqrt (cos phi1))))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
t_2)))))
(*
(* R 2.0)
(atan2
(hypot t_0 (* (sqrt (* (cos phi1) (cos phi2))) t_1))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos lambda1))))
t_2))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = sin((0.5 * (lambda1 - lambda2)));
double t_2 = pow(t_0, 2.0);
double tmp;
if ((lambda2 <= -3.4e-25) || !(lambda2 <= 2.75e-8)) {
tmp = (R * 2.0) * atan2(hypot(sin((0.5 * phi1)), (t_1 * sqrt(cos(phi1)))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), t_2))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_0, (sqrt((cos(phi1) * cos(phi2))) * t_1)), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos(lambda1)))), t_2))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_2 = t_0 ^ 2.0 tmp = 0.0 if ((lambda2 <= -3.4e-25) || !(lambda2 <= 2.75e-8)) tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(0.5 * phi1)), Float64(t_1 * sqrt(cos(phi1)))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), t_2))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(sqrt(Float64(cos(phi1) * cos(phi2))) * t_1)), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(lambda1)))), t_2))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[t$95$0, 2.0], $MachinePrecision]}, If[Or[LessEqual[lambda2, -3.4e-25], N[Not[LessEqual[lambda2, 2.75e-8]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$1 * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[lambda1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $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)\\
t_1 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_2 := {t\_0}^{2}\\
\mathbf{if}\;\lambda_2 \leq -3.4 \cdot 10^{-25} \lor \neg \left(\lambda_2 \leq 2.75 \cdot 10^{-8}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \phi_1\right), t\_1 \cdot \sqrt{\cos \phi_1}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), t\_2\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, \sqrt{\cos \phi_1 \cdot \cos \phi_2} \cdot t\_1\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \lambda_1\right), t\_2\right)}}\\
\end{array}
\end{array}
if lambda2 < -3.40000000000000002e-25 or 2.7500000000000001e-8 < lambda2 Initial program 49.4%
associate-*r*49.4%
*-commutative49.4%
Simplified49.4%
Applied egg-rr32.6%
*-lft-identity32.6%
*-commutative32.6%
*-commutative32.6%
metadata-eval32.6%
cancel-sign-sub-inv32.6%
Simplified32.6%
Taylor expanded in phi2 around 0 27.5%
Taylor expanded in phi2 around 0 30.9%
if -3.40000000000000002e-25 < lambda2 < 2.7500000000000001e-8Initial program 79.3%
associate-*r*79.3%
*-commutative79.3%
Simplified79.3%
Applied egg-rr52.0%
*-lft-identity52.0%
*-commutative52.0%
*-commutative52.0%
metadata-eval52.0%
cancel-sign-sub-inv52.0%
Simplified52.0%
Taylor expanded in lambda2 around 0 52.0%
Final simplification40.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(pow t_0 2.0))))))
(if (or (<= lambda2 -3.4e-25) (not (<= lambda2 3e-15)))
(*
(* R 2.0)
(atan2
(hypot
(sin (* 0.5 phi1))
(* (sin (* 0.5 (- lambda1 lambda2))) (sqrt (cos phi1))))
t_1))
(*
(* R 2.0)
(atan2
(hypot t_0 (* (sqrt (* (cos phi1) (cos phi2))) (sin (* 0.5 lambda1))))
t_1)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), pow(t_0, 2.0))));
double tmp;
if ((lambda2 <= -3.4e-25) || !(lambda2 <= 3e-15)) {
tmp = (R * 2.0) * atan2(hypot(sin((0.5 * phi1)), (sin((0.5 * (lambda1 - lambda2))) * sqrt(cos(phi1)))), t_1);
} else {
tmp = (R * 2.0) * atan2(hypot(t_0, (sqrt((cos(phi1) * cos(phi2))) * sin((0.5 * lambda1)))), t_1);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), (t_0 ^ 2.0)))) tmp = 0.0 if ((lambda2 <= -3.4e-25) || !(lambda2 <= 3e-15)) tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(0.5 * phi1)), Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(cos(phi1)))), t_1)); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(sqrt(Float64(cos(phi1) * cos(phi2))) * sin(Float64(0.5 * lambda1)))), t_1)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda2, -3.4e-25], N[Not[LessEqual[lambda2, 3e-15]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {t\_0}^{2}\right)}\\
\mathbf{if}\;\lambda_2 \leq -3.4 \cdot 10^{-25} \lor \neg \left(\lambda_2 \leq 3 \cdot 10^{-15}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \phi_1\right), \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_1}\right)}{t\_1}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, \sqrt{\cos \phi_1 \cdot \cos \phi_2} \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}{t\_1}\\
\end{array}
\end{array}
if lambda2 < -3.40000000000000002e-25 or 3e-15 < lambda2 Initial program 49.4%
associate-*r*49.4%
*-commutative49.4%
Simplified49.4%
Applied egg-rr32.6%
*-lft-identity32.6%
*-commutative32.6%
*-commutative32.6%
metadata-eval32.6%
cancel-sign-sub-inv32.6%
Simplified32.6%
Taylor expanded in phi2 around 0 27.5%
Taylor expanded in phi2 around 0 30.9%
if -3.40000000000000002e-25 < lambda2 < 3e-15Initial program 79.3%
associate-*r*79.3%
*-commutative79.3%
Simplified79.3%
Applied egg-rr52.0%
*-lft-identity52.0%
*-commutative52.0%
*-commutative52.0%
metadata-eval52.0%
cancel-sign-sub-inv52.0%
Simplified52.0%
Taylor expanded in lambda2 around 0 51.2%
Final simplification40.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* 0.5 (- lambda1 lambda2))))
(t_2 (* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2))))))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (sin (* 0.5 (- phi1 phi2)))))
(if (<= phi1 -6.5e-6)
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* t_3 t_3)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (* (cos phi1) (pow t_1 2.0)))))))
(if (<= phi1 4e-5)
(*
(* R 2.0)
(atan2
(hypot t_4 (* (sqrt t_0) t_1))
(sqrt (- 1.0 (fma (cos phi1) t_2 (pow (sin (* phi2 -0.5)) 2.0))))))
(*
(* R 2.0)
(atan2
(hypot (sin (* 0.5 phi1)) (* t_1 (sqrt (cos phi1))))
(sqrt (- 1.0 (fma (cos phi1) t_2 (pow t_4 2.0))))))))))
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 * (lambda1 - lambda2)));
double t_2 = cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = sin((0.5 * (phi1 - phi2)));
double tmp;
if (phi1 <= -6.5e-6) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_3 * t_3)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (cos(phi1) * pow(t_1, 2.0))))));
} else if (phi1 <= 4e-5) {
tmp = (R * 2.0) * atan2(hypot(t_4, (sqrt(t_0) * t_1)), sqrt((1.0 - fma(cos(phi1), t_2, pow(sin((phi2 * -0.5)), 2.0)))));
} else {
tmp = (R * 2.0) * atan2(hypot(sin((0.5 * phi1)), (t_1 * sqrt(cos(phi1)))), sqrt((1.0 - fma(cos(phi1), t_2, pow(t_4, 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_2 = Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = sin(Float64(0.5 * Float64(phi1 - phi2))) tmp = 0.0 if (phi1 <= -6.5e-6) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_3 * t_3)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(cos(phi1) * (t_1 ^ 2.0))))))); elseif (phi1 <= 4e-5) tmp = Float64(Float64(R * 2.0) * atan(hypot(t_4, Float64(sqrt(t_0) * t_1)), sqrt(Float64(1.0 - fma(cos(phi1), t_2, (sin(Float64(phi2 * -0.5)) ^ 2.0)))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(0.5 * phi1)), Float64(t_1 * sqrt(cos(phi1)))), sqrt(Float64(1.0 - fma(cos(phi1), t_2, (t_4 ^ 2.0)))))); 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -6.5e-6], 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[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 4e-5], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$4 ^ 2 + N[(N[Sqrt[t$95$0], $MachinePrecision] * t$95$1), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$2 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$1 * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$2 + N[Power[t$95$4, 2.0], $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(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_2 := \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
\mathbf{if}\;\phi_1 \leq -6.5 \cdot 10^{-6}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_3 \cdot t\_3\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \cos \phi_1 \cdot {t\_1}^{2}}}\right)\\
\mathbf{elif}\;\phi_1 \leq 4 \cdot 10^{-5}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_4, \sqrt{t\_0} \cdot t\_1\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \phi_1\right), t\_1 \cdot \sqrt{\cos \phi_1}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_2, {t\_4}^{2}\right)}}\\
\end{array}
\end{array}
if phi1 < -6.4999999999999996e-6Initial program 46.5%
associate-*l*46.5%
Simplified46.5%
Taylor expanded in phi1 around 0 19.1%
unpow219.1%
1-sub-sin19.1%
unpow219.1%
*-commutative19.1%
metadata-eval19.1%
distribute-rgt-neg-in19.1%
cos-neg19.1%
Simplified19.1%
Taylor expanded in phi2 around 0 20.3%
if -6.4999999999999996e-6 < phi1 < 4.00000000000000033e-5Initial program 75.1%
associate-*r*75.1%
*-commutative75.1%
Simplified75.1%
Applied egg-rr56.8%
*-lft-identity56.8%
*-commutative56.8%
*-commutative56.8%
metadata-eval56.8%
cancel-sign-sub-inv56.8%
Simplified56.8%
Taylor expanded in phi1 around 0 56.6%
*-commutative56.6%
Simplified56.6%
if 4.00000000000000033e-5 < phi1 Initial program 50.9%
associate-*r*50.9%
*-commutative50.9%
Simplified50.9%
Applied egg-rr27.8%
*-lft-identity27.8%
*-commutative27.8%
*-commutative27.8%
metadata-eval27.8%
cancel-sign-sub-inv27.8%
Simplified27.8%
Taylor expanded in phi2 around 0 27.8%
Taylor expanded in phi2 around 0 28.9%
Final simplification41.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (sqrt (* (cos phi1) (cos phi2))))
(t_2 (hypot t_0 (* t_1 (sin (* 0.5 (- lambda1 lambda2))))))
(t_3 (pow t_0 2.0)))
(if (<= lambda1 -8.4e+55)
(*
(* R 2.0)
(atan2
(hypot t_0 (* t_1 (sin (* 0.5 lambda1))))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
t_3)))))
(if (<= lambda1 1.05e-6)
(*
(* R 2.0)
(atan2
t_2
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos lambda2))))
t_3)))))
(*
(* R 2.0)
(atan2
t_2
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos lambda1))))
t_3)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = sqrt((cos(phi1) * cos(phi2)));
double t_2 = hypot(t_0, (t_1 * sin((0.5 * (lambda1 - lambda2)))));
double t_3 = pow(t_0, 2.0);
double tmp;
if (lambda1 <= -8.4e+55) {
tmp = (R * 2.0) * atan2(hypot(t_0, (t_1 * sin((0.5 * lambda1)))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), t_3))));
} else if (lambda1 <= 1.05e-6) {
tmp = (R * 2.0) * atan2(t_2, sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos(lambda2)))), t_3))));
} else {
tmp = (R * 2.0) * atan2(t_2, sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos(lambda1)))), t_3))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sqrt(Float64(cos(phi1) * cos(phi2))) t_2 = hypot(t_0, Float64(t_1 * sin(Float64(0.5 * Float64(lambda1 - lambda2))))) t_3 = t_0 ^ 2.0 tmp = 0.0 if (lambda1 <= -8.4e+55) tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(t_1 * sin(Float64(0.5 * lambda1)))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), t_3))))); elseif (lambda1 <= 1.05e-6) tmp = Float64(Float64(R * 2.0) * atan(t_2, sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(lambda2)))), t_3))))); else tmp = Float64(Float64(R * 2.0) * atan(t_2, sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(lambda1)))), t_3))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[t$95$0 ^ 2 + N[(t$95$1 * N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]}, Block[{t$95$3 = N[Power[t$95$0, 2.0], $MachinePrecision]}, If[LessEqual[lambda1, -8.4e+55], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(t$95$1 * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 1.05e-6], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[lambda1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $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)\\
t_1 := \sqrt{\cos \phi_1 \cdot \cos \phi_2}\\
t_2 := \mathsf{hypot}\left(t\_0, t\_1 \cdot \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right)\\
t_3 := {t\_0}^{2}\\
\mathbf{if}\;\lambda_1 \leq -8.4 \cdot 10^{+55}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, t\_1 \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), t\_3\right)}}\\
\mathbf{elif}\;\lambda_1 \leq 1.05 \cdot 10^{-6}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \lambda_2\right), t\_3\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \lambda_1\right), t\_3\right)}}\\
\end{array}
\end{array}
if lambda1 < -8.4000000000000002e55Initial program 48.7%
associate-*r*48.7%
*-commutative48.7%
Simplified48.8%
Applied egg-rr35.9%
*-lft-identity35.9%
*-commutative35.9%
*-commutative35.9%
metadata-eval35.9%
cancel-sign-sub-inv35.9%
Simplified35.9%
Taylor expanded in lambda2 around 0 36.1%
if -8.4000000000000002e55 < lambda1 < 1.0499999999999999e-6Initial program 76.6%
associate-*r*76.6%
*-commutative76.6%
Simplified76.6%
Applied egg-rr47.3%
*-lft-identity47.3%
*-commutative47.3%
*-commutative47.3%
metadata-eval47.3%
cancel-sign-sub-inv47.3%
Simplified47.3%
Taylor expanded in lambda1 around 0 47.3%
cos-neg47.3%
Simplified47.3%
if 1.0499999999999999e-6 < lambda1 Initial program 43.9%
associate-*r*43.9%
*-commutative43.9%
Simplified43.9%
Applied egg-rr32.7%
*-lft-identity32.7%
*-commutative32.7%
*-commutative32.7%
metadata-eval32.7%
cancel-sign-sub-inv32.7%
Simplified32.7%
Taylor expanded in lambda2 around 0 32.8%
Final simplification41.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2)))))
(*
(* R 2.0)
(atan2
(hypot
t_0
(* (sqrt (* (cos phi1) (cos phi2))) (sin (* 0.5 (- lambda1 lambda2)))))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(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(hypot(t_0, (sqrt((cos(phi1) * cos(phi2))) * sin((0.5 * (lambda1 - lambda2))))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), pow(t_0, 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) return Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(sqrt(Float64(cos(phi1) * cos(phi2))) * sin(Float64(0.5 * Float64(lambda1 - lambda2))))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), (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[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $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)\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, \sqrt{\cos \phi_1 \cdot \cos \phi_2} \cdot \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {t\_0}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.9%
associate-*r*62.9%
*-commutative62.9%
Simplified63.0%
Applied egg-rr41.4%
*-lft-identity41.4%
*-commutative41.4%
*-commutative41.4%
metadata-eval41.4%
cancel-sign-sub-inv41.4%
Simplified41.4%
Final simplification41.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -8.5e-36) (not (<= phi2 1.4e-15)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_1 t_1))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (* (cos phi1) (pow t_0 2.0)))))))
(*
(* R 2.0)
(atan2
(hypot (sin (* 0.5 phi1)) (* t_0 (sqrt (cos phi1))))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -8.5e-36) || !(phi2 <= 1.4e-15)) {
tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_1 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (cos(phi1) * pow(t_0, 2.0))))));
} else {
tmp = (R * 2.0) * atan2(hypot(sin((0.5 * phi1)), (t_0 * sqrt(cos(phi1)))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -8.5e-36) || !(phi2 <= 1.4e-15)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(cos(phi1) * (t_0 ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(0.5 * phi1)), Float64(t_0 * sqrt(cos(phi1)))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -8.5e-36], N[Not[LessEqual[phi2, 1.4e-15]], $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$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$0 * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -8.5 \cdot 10^{-36} \lor \neg \left(\phi_2 \leq 1.4 \cdot 10^{-15}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \cos \phi_1 \cdot {t\_0}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \phi_1\right), t\_0 \cdot \sqrt{\cos \phi_1}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -8.5000000000000007e-36 or 1.40000000000000007e-15 < phi2 Initial program 53.0%
associate-*l*52.9%
Simplified52.9%
Taylor expanded in phi1 around 0 51.5%
unpow251.5%
1-sub-sin51.6%
unpow251.6%
*-commutative51.6%
metadata-eval51.6%
distribute-rgt-neg-in51.6%
cos-neg51.6%
Simplified51.6%
Taylor expanded in phi2 around 0 22.8%
if -8.5000000000000007e-36 < phi2 < 1.40000000000000007e-15Initial program 74.1%
associate-*r*74.1%
*-commutative74.1%
Simplified74.1%
Applied egg-rr55.7%
*-lft-identity55.7%
*-commutative55.7%
*-commutative55.7%
metadata-eval55.7%
cancel-sign-sub-inv55.7%
Simplified55.7%
Taylor expanded in phi2 around 0 55.7%
Taylor expanded in phi2 around 0 55.7%
Final simplification38.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(- 1.0 (* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 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(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return 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((1.0 - (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return 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((1.0 - (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(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[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $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)\\
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{1 - \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 62.9%
associate-*l*62.9%
Simplified63.0%
Taylor expanded in phi1 around 0 49.4%
unpow249.4%
1-sub-sin49.4%
unpow249.4%
*-commutative49.4%
metadata-eval49.4%
distribute-rgt-neg-in49.4%
cos-neg49.4%
Simplified49.4%
Taylor expanded in phi2 around 0 34.3%
Final simplification34.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2)))))
(*
R
(*
2.0
(atan2
(sqrt
(+ (pow (sin (* phi2 -0.5)) 2.0) (* (cos phi2) (* t_0 (fabs t_0)))))
(sqrt (- 1.0 (* (cos phi1) (pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
return R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + (cos(phi2) * (t_0 * fabs(t_0))))), sqrt((1.0 - (cos(phi1) * 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 * (lambda1 - lambda2)))
code = r * (2.0d0 * atan2(sqrt(((sin((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * (t_0 * abs(t_0))))), sqrt((1.0d0 - (cos(phi1) * (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 * (lambda1 - lambda2)));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * (t_0 * Math.abs(t_0))))), Math.sqrt((1.0 - (Math.cos(phi1) * Math.pow(t_0, 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (lambda1 - lambda2))) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi2 * -0.5)), 2.0) + (math.cos(phi2) * (t_0 * math.fabs(t_0))))), math.sqrt((1.0 - (math.cos(phi1) * math.pow(t_0, 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(t_0 * abs(t_0))))), sqrt(Float64(1.0 - Float64(cos(phi1) * (t_0 ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))); tmp = R * (2.0 * atan2(sqrt(((sin((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * (t_0 * abs(t_0))))), sqrt((1.0 - (cos(phi1) * (t_0 ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(t$95$0 * N[Abs[t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $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(\lambda_1 - \lambda_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \left(t\_0 \cdot \left|t\_0\right|\right)}}{\sqrt{1 - \cos \phi_1 \cdot {t\_0}^{2}}}\right)
\end{array}
\end{array}
Initial program 62.9%
add-sqr-sqrt29.8%
sqrt-prod45.1%
rem-sqrt-square45.1%
div-inv45.1%
metadata-eval45.1%
Applied egg-rr45.1%
Taylor expanded in phi1 around 0 36.4%
Taylor expanded in phi1 around 0 32.2%
Taylor expanded in phi2 around 0 20.9%
Final simplification20.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(*
(sin (* 0.5 (- lambda1 lambda2)))
(+
1.0
(* (pow phi2 2.0) (- (* (pow phi2 2.0) -0.010416666666666666) 0.25))))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * atan2((sin((0.5 * (lambda1 - lambda2))) * (1.0 + (pow(phi2, 2.0) * ((pow(phi2, 2.0) * -0.010416666666666666) - 0.25)))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * 2.0) * atan(Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * Float64(1.0 + Float64((phi2 ^ 2.0) * Float64(Float64((phi2 ^ 2.0) * -0.010416666666666666) - 0.25)))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(1.0 + N[(N[Power[phi2, 2.0], $MachinePrecision] * N[(N[(N[Power[phi2, 2.0], $MachinePrecision] * -0.010416666666666666), $MachinePrecision] - 0.25), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \left(1 + {\phi_2}^{2} \cdot \left({\phi_2}^{2} \cdot -0.010416666666666666 - 0.25\right)\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}
\end{array}
Initial program 62.9%
associate-*r*62.9%
*-commutative62.9%
Simplified63.0%
Applied egg-rr41.4%
*-lft-identity41.4%
*-commutative41.4%
*-commutative41.4%
metadata-eval41.4%
cancel-sign-sub-inv41.4%
Simplified41.4%
Taylor expanded in phi2 around 0 31.8%
Taylor expanded in phi1 around 0 13.8%
Taylor expanded in phi2 around 0 16.3%
Final simplification16.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(* (sin (* 0.5 (- lambda1 lambda2))) (+ 1.0 (* (pow phi2 2.0) -0.25)))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * atan2((sin((0.5 * (lambda1 - lambda2))) * (1.0 + (pow(phi2, 2.0) * -0.25))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * 2.0) * atan(Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * Float64(1.0 + Float64((phi2 ^ 2.0) * -0.25))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(1.0 + N[(N[Power[phi2, 2.0], $MachinePrecision] * -0.25), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \left(1 + {\phi_2}^{2} \cdot -0.25\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}
\end{array}
Initial program 62.9%
associate-*r*62.9%
*-commutative62.9%
Simplified63.0%
Applied egg-rr41.4%
*-lft-identity41.4%
*-commutative41.4%
*-commutative41.4%
metadata-eval41.4%
cancel-sign-sub-inv41.4%
Simplified41.4%
Taylor expanded in phi2 around 0 31.8%
Taylor expanded in phi1 around 0 13.8%
Taylor expanded in phi2 around 0 16.3%
*-commutative16.3%
Simplified16.3%
Final simplification16.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(sin (* 0.5 (- lambda1 lambda2)))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * atan2(sin((0.5 * (lambda1 - lambda2))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * 2.0) * atan(sin(Float64(0.5 * Float64(lambda1 - lambda2))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}
\end{array}
Initial program 62.9%
associate-*r*62.9%
*-commutative62.9%
Simplified63.0%
Applied egg-rr41.4%
*-lft-identity41.4%
*-commutative41.4%
*-commutative41.4%
metadata-eval41.4%
cancel-sign-sub-inv41.4%
Simplified41.4%
Taylor expanded in phi2 around 0 31.8%
Taylor expanded in phi1 around 0 13.8%
Taylor expanded in phi2 around 0 16.2%
Final simplification16.2%
herbie shell --seed 2024185
(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))))))))))