
(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 22 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma (cos (* -0.5 phi2)) t_0 (* (sin (* -0.5 phi2)) t_1)) 2.0)
(* t_2 (* t_3 t_3))))
(sqrt
(+
(-
1.0
(pow (- (* t_0 (cos (* phi2 0.5))) (* t_1 (sin (* phi2 0.5)))) 2.0))
(*
t_2
(-
(/
(+ (* (cos lambda2) (cos lambda1)) (* (sin lambda2) (sin lambda1)))
2.0)
0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(cos((-0.5 * phi2)), t_0, (sin((-0.5 * phi2)) * t_1)), 2.0) + (t_2 * (t_3 * t_3)))), sqrt(((1.0 - pow(((t_0 * cos((phi2 * 0.5))) - (t_1 * sin((phi2 * 0.5)))), 2.0)) + (t_2 * ((((cos(lambda2) * cos(lambda1)) + (sin(lambda2) * sin(lambda1))) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(cos(Float64(-0.5 * phi2)), t_0, Float64(sin(Float64(-0.5 * phi2)) * t_1)) ^ 2.0) + Float64(t_2 * Float64(t_3 * t_3)))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_0 * cos(Float64(phi2 * 0.5))) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) + Float64(t_2 * Float64(Float64(Float64(Float64(cos(lambda2) * cos(lambda1)) + Float64(sin(lambda2) * sin(lambda1))) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(N[(N[(N[(N[Cos[lambda2], $MachinePrecision] * N[Cos[lambda1], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[lambda2], $MachinePrecision] * N[Sin[lambda1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_0, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_1\right)\right)}^{2} + t\_2 \cdot \left(t\_3 \cdot t\_3\right)}}{\sqrt{\left(1 - {\left(t\_0 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) + t\_2 \cdot \left(\frac{\cos \lambda_2 \cdot \cos \lambda_1 + \sin \lambda_2 \cdot \sin \lambda_1}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 60.9%
associate-*l*61.0%
Simplified61.0%
div-sub61.0%
sin-diff62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
Applied egg-rr62.2%
div-sub61.0%
sin-diff62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
Applied egg-rr76.5%
*-commutative76.5%
*-commutative76.5%
fma-neg76.5%
cos-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
distribute-lft-neg-in76.5%
sin-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
*-commutative76.5%
Simplified76.5%
sin-mult76.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
cos-sum76.5%
cos-276.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
Applied egg-rr76.5%
div-sub76.5%
+-inverses76.5%
cos-076.5%
metadata-eval76.5%
associate-*r*76.5%
metadata-eval76.5%
*-lft-identity76.5%
sub-neg76.5%
mul-1-neg76.5%
cos-neg76.5%
+-commutative76.5%
distribute-neg-in76.5%
mul-1-neg76.5%
remove-double-neg76.5%
sub-neg76.5%
Simplified76.5%
cos-diff77.3%
Applied egg-rr77.3%
Final simplification77.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (sin (* 0.5 (- phi1 phi2))))
(t_4 (* (cos phi1) (cos phi2)))
(t_5 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_2 (* t_4 t_2))))
(t_6 (/ (cos (- lambda2 lambda1)) 2.0)))
(if (<= (atan2 (sqrt t_5) (sqrt (- 1.0 t_5))) 0.01)
(*
(atan2
(hypot
t_3
(*
(+ (sin (* 0.5 lambda1)) (* (* -0.5 lambda2) (cos (* 0.5 lambda1))))
(sqrt t_4)))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow t_3 2.0)))))
(* R 2.0))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma (cos (* -0.5 phi2)) t_0 (* (sin (* -0.5 phi2)) t_1)) 2.0)
(* t_4 (- 0.5 t_6))))
(sqrt
(+
(-
1.0
(pow (- (* t_0 (cos (* phi2 0.5))) (* t_1 (sin (* phi2 0.5)))) 2.0))
(* t_4 (- t_6 0.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = sin((0.5 * (phi1 - phi2)));
double t_4 = cos(phi1) * cos(phi2);
double t_5 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_2 * (t_4 * t_2));
double t_6 = cos((lambda2 - lambda1)) / 2.0;
double tmp;
if (atan2(sqrt(t_5), sqrt((1.0 - t_5))) <= 0.01) {
tmp = atan2(hypot(t_3, ((sin((0.5 * lambda1)) + ((-0.5 * lambda2) * cos((0.5 * lambda1)))) * sqrt(t_4))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(t_3, 2.0))))) * (R * 2.0);
} else {
tmp = R * (2.0 * atan2(sqrt((pow(fma(cos((-0.5 * phi2)), t_0, (sin((-0.5 * phi2)) * t_1)), 2.0) + (t_4 * (0.5 - t_6)))), sqrt(((1.0 - pow(((t_0 * cos((phi2 * 0.5))) - (t_1 * sin((phi2 * 0.5)))), 2.0)) + (t_4 * (t_6 - 0.5))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_4 = Float64(cos(phi1) * cos(phi2)) t_5 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_2 * Float64(t_4 * t_2))) t_6 = Float64(cos(Float64(lambda2 - lambda1)) / 2.0) tmp = 0.0 if (atan(sqrt(t_5), sqrt(Float64(1.0 - t_5))) <= 0.01) tmp = Float64(atan(hypot(t_3, Float64(Float64(sin(Float64(0.5 * lambda1)) + Float64(Float64(-0.5 * lambda2) * cos(Float64(0.5 * lambda1)))) * sqrt(t_4))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (t_3 ^ 2.0))))) * Float64(R * 2.0)); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(cos(Float64(-0.5 * phi2)), t_0, Float64(sin(Float64(-0.5 * phi2)) * t_1)) ^ 2.0) + Float64(t_4 * Float64(0.5 - t_6)))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_0 * cos(Float64(phi2 * 0.5))) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) + Float64(t_4 * Float64(t_6 - 0.5))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$4 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]}, If[LessEqual[N[ArcTan[N[Sqrt[t$95$5], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$5), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 0.01], N[(N[ArcTan[N[Sqrt[t$95$3 ^ 2 + N[(N[(N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision] + N[(N[(-0.5 * lambda2), $MachinePrecision] * N[Cos[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[t$95$4], $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$3, 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[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$4 * N[(0.5 - t$95$6), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$4 * N[(t$95$6 - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_4 := \cos \phi_1 \cdot \cos \phi_2\\
t_5 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_2 \cdot \left(t\_4 \cdot t\_2\right)\\
t_6 := \frac{\cos \left(\lambda_2 - \lambda_1\right)}{2}\\
\mathbf{if}\;\tan^{-1}_* \frac{\sqrt{t\_5}}{\sqrt{1 - t\_5}} \leq 0.01:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(t\_3, \left(\sin \left(0.5 \cdot \lambda_1\right) + \left(-0.5 \cdot \lambda_2\right) \cdot \cos \left(0.5 \cdot \lambda_1\right)\right) \cdot \sqrt{t\_4}\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}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_0, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_1\right)\right)}^{2} + t\_4 \cdot \left(0.5 - t\_6\right)}}{\sqrt{\left(1 - {\left(t\_0 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) + t\_4 \cdot \left(t\_6 - 0.5\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)))))))) < 0.0100000000000000002Initial program 84.9%
associate-*r*84.9%
*-commutative84.9%
Simplified84.9%
Applied egg-rr94.1%
*-lft-identity94.1%
*-commutative94.1%
*-commutative94.1%
*-commutative94.1%
Simplified94.1%
Taylor expanded in lambda2 around 0 94.7%
associate-*r*94.7%
*-commutative94.7%
Simplified94.7%
if 0.0100000000000000002 < (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 59.5%
associate-*l*59.5%
Simplified59.5%
div-sub59.5%
sin-diff60.8%
div-inv60.8%
metadata-eval60.8%
div-inv60.8%
metadata-eval60.8%
div-inv60.8%
metadata-eval60.8%
div-inv60.8%
metadata-eval60.8%
Applied egg-rr60.8%
div-sub59.5%
sin-diff60.8%
div-inv60.8%
metadata-eval60.8%
div-inv60.8%
metadata-eval60.8%
div-inv60.8%
metadata-eval60.8%
div-inv60.8%
metadata-eval60.8%
Applied egg-rr76.0%
*-commutative76.0%
*-commutative76.0%
fma-neg76.0%
cos-neg76.0%
distribute-rgt-neg-in76.0%
metadata-eval76.0%
*-commutative76.0%
*-commutative76.0%
*-commutative76.0%
*-commutative76.0%
distribute-lft-neg-in76.0%
sin-neg76.0%
distribute-rgt-neg-in76.0%
metadata-eval76.0%
*-commutative76.0%
*-commutative76.0%
Simplified76.0%
sin-mult76.0%
div-inv76.0%
metadata-eval76.0%
*-commutative76.0%
div-inv76.0%
metadata-eval76.0%
*-commutative76.0%
cos-sum76.0%
cos-276.0%
div-inv76.0%
metadata-eval76.0%
*-commutative76.0%
Applied egg-rr76.0%
div-sub76.0%
+-inverses76.0%
cos-076.0%
metadata-eval76.0%
associate-*r*76.0%
metadata-eval76.0%
*-lft-identity76.0%
sub-neg76.0%
mul-1-neg76.0%
cos-neg76.0%
+-commutative76.0%
distribute-neg-in76.0%
mul-1-neg76.0%
remove-double-neg76.0%
sub-neg76.0%
Simplified76.0%
sin-mult76.0%
div-inv76.0%
metadata-eval76.0%
*-commutative76.0%
div-inv76.0%
metadata-eval76.0%
*-commutative76.0%
cos-sum76.0%
cos-276.0%
div-inv76.0%
metadata-eval76.0%
*-commutative76.0%
Applied egg-rr75.9%
div-sub76.0%
+-inverses76.0%
cos-076.0%
metadata-eval76.0%
associate-*r*76.0%
metadata-eval76.0%
*-lft-identity76.0%
sub-neg76.0%
mul-1-neg76.0%
cos-neg76.0%
+-commutative76.0%
distribute-neg-in76.0%
mul-1-neg76.0%
remove-double-neg76.0%
sub-neg76.0%
Simplified75.9%
Final simplification77.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma (cos (* -0.5 phi2)) t_0 (* (sin (* -0.5 phi2)) t_1)) 2.0)
(* t_2 (* t_3 t_3))))
(sqrt
(+
(-
1.0
(pow (- (* t_0 (cos (* phi2 0.5))) (* t_1 (sin (* phi2 0.5)))) 2.0))
(* t_2 (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(cos((-0.5 * phi2)), t_0, (sin((-0.5 * phi2)) * t_1)), 2.0) + (t_2 * (t_3 * t_3)))), sqrt(((1.0 - pow(((t_0 * cos((phi2 * 0.5))) - (t_1 * sin((phi2 * 0.5)))), 2.0)) + (t_2 * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(cos(Float64(-0.5 * phi2)), t_0, Float64(sin(Float64(-0.5 * phi2)) * t_1)) ^ 2.0) + Float64(t_2 * Float64(t_3 * t_3)))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_0 * cos(Float64(phi2 * 0.5))) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) + Float64(t_2 * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_0, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_1\right)\right)}^{2} + t\_2 \cdot \left(t\_3 \cdot t\_3\right)}}{\sqrt{\left(1 - {\left(t\_0 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) + t\_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 60.9%
associate-*l*61.0%
Simplified61.0%
div-sub61.0%
sin-diff62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
Applied egg-rr62.2%
div-sub61.0%
sin-diff62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
Applied egg-rr76.5%
*-commutative76.5%
*-commutative76.5%
fma-neg76.5%
cos-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
distribute-lft-neg-in76.5%
sin-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
*-commutative76.5%
Simplified76.5%
sin-mult76.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
cos-sum76.5%
cos-276.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
Applied egg-rr76.5%
div-sub76.5%
+-inverses76.5%
cos-076.5%
metadata-eval76.5%
associate-*r*76.5%
metadata-eval76.5%
*-lft-identity76.5%
sub-neg76.5%
mul-1-neg76.5%
cos-neg76.5%
+-commutative76.5%
distribute-neg-in76.5%
mul-1-neg76.5%
remove-double-neg76.5%
sub-neg76.5%
Simplified76.5%
Final simplification76.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (sin (* phi1 0.5)))
(t_2 (cos (* phi1 0.5)))
(t_3
(pow (fma (cos (* -0.5 phi2)) t_1 (* (sin (* -0.5 phi2)) t_2)) 2.0))
(t_4
(sqrt
(+
(-
1.0
(pow
(- (* t_1 (cos (* phi2 0.5))) (* t_2 (sin (* phi2 0.5))))
2.0))
(*
(* (cos phi1) (cos phi2))
(- (/ (cos (- lambda2 lambda1)) 2.0) 0.5))))))
(if (or (<= phi1 -50000000000000.0) (not (<= phi1 1.1e+29)))
(* R (* 2.0 (atan2 (sqrt (+ t_3 (* (cos phi1) t_0))) t_4)))
(* R (* 2.0 (atan2 (sqrt (+ t_3 (* (cos phi2) t_0))) t_4))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin((phi1 * 0.5));
double t_2 = cos((phi1 * 0.5));
double t_3 = pow(fma(cos((-0.5 * phi2)), t_1, (sin((-0.5 * phi2)) * t_2)), 2.0);
double t_4 = sqrt(((1.0 - pow(((t_1 * cos((phi2 * 0.5))) - (t_2 * sin((phi2 * 0.5)))), 2.0)) + ((cos(phi1) * cos(phi2)) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))));
double tmp;
if ((phi1 <= -50000000000000.0) || !(phi1 <= 1.1e+29)) {
tmp = R * (2.0 * atan2(sqrt((t_3 + (cos(phi1) * t_0))), t_4));
} else {
tmp = R * (2.0 * atan2(sqrt((t_3 + (cos(phi2) * t_0))), t_4));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(phi1 * 0.5)) t_2 = cos(Float64(phi1 * 0.5)) t_3 = fma(cos(Float64(-0.5 * phi2)), t_1, Float64(sin(Float64(-0.5 * phi2)) * t_2)) ^ 2.0 t_4 = sqrt(Float64(Float64(1.0 - (Float64(Float64(t_1 * cos(Float64(phi2 * 0.5))) - Float64(t_2 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5)))) tmp = 0.0 if ((phi1 <= -50000000000000.0) || !(phi1 <= 1.1e+29)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + Float64(cos(phi1) * t_0))), t_4))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + Float64(cos(phi2) * t_0))), t_4))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$1 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$2 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -50000000000000.0], N[Not[LessEqual[phi1, 1.1e+29]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_3 := {\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_1, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_2\right)\right)}^{2}\\
t_4 := \sqrt{\left(1 - {\left(t\_1 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_2 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}\\
\mathbf{if}\;\phi_1 \leq -50000000000000 \lor \neg \left(\phi_1 \leq 1.1 \cdot 10^{+29}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + \cos \phi_1 \cdot t\_0}}{t\_4}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + \cos \phi_2 \cdot t\_0}}{t\_4}\right)\\
\end{array}
\end{array}
if phi1 < -5e13 or 1.1000000000000001e29 < phi1 Initial program 48.7%
associate-*l*48.8%
Simplified48.8%
div-sub48.8%
sin-diff51.5%
div-inv51.5%
metadata-eval51.5%
div-inv51.5%
metadata-eval51.5%
div-inv51.5%
metadata-eval51.5%
div-inv51.5%
metadata-eval51.5%
Applied egg-rr51.5%
div-sub48.8%
sin-diff51.5%
div-inv51.5%
metadata-eval51.5%
div-inv51.5%
metadata-eval51.5%
div-inv51.5%
metadata-eval51.5%
div-inv51.5%
metadata-eval51.5%
Applied egg-rr81.7%
*-commutative81.7%
*-commutative81.7%
fma-neg81.7%
cos-neg81.7%
distribute-rgt-neg-in81.7%
metadata-eval81.7%
*-commutative81.7%
*-commutative81.7%
*-commutative81.7%
*-commutative81.7%
distribute-lft-neg-in81.7%
sin-neg81.7%
distribute-rgt-neg-in81.7%
metadata-eval81.7%
*-commutative81.7%
*-commutative81.7%
Simplified81.7%
sin-mult81.7%
div-inv81.7%
metadata-eval81.7%
*-commutative81.7%
div-inv81.7%
metadata-eval81.7%
*-commutative81.7%
cos-sum81.7%
cos-281.7%
div-inv81.7%
metadata-eval81.7%
*-commutative81.7%
Applied egg-rr81.7%
div-sub81.7%
+-inverses81.7%
cos-081.7%
metadata-eval81.7%
associate-*r*81.7%
metadata-eval81.7%
*-lft-identity81.7%
sub-neg81.7%
mul-1-neg81.7%
cos-neg81.7%
+-commutative81.7%
distribute-neg-in81.7%
mul-1-neg81.7%
remove-double-neg81.7%
sub-neg81.7%
Simplified81.7%
Taylor expanded in phi2 around 0 63.7%
*-commutative63.7%
Simplified63.7%
if -5e13 < phi1 < 1.1000000000000001e29Initial program 70.6%
associate-*l*70.6%
Simplified70.6%
div-sub70.6%
sin-diff70.7%
div-inv70.7%
metadata-eval70.7%
div-inv70.7%
metadata-eval70.7%
div-inv70.7%
metadata-eval70.7%
div-inv70.7%
metadata-eval70.7%
Applied egg-rr70.7%
div-sub70.6%
sin-diff70.7%
div-inv70.7%
metadata-eval70.7%
div-inv70.7%
metadata-eval70.7%
div-inv70.7%
metadata-eval70.7%
div-inv70.7%
metadata-eval70.7%
Applied egg-rr72.4%
*-commutative72.4%
*-commutative72.4%
fma-neg72.4%
cos-neg72.4%
distribute-rgt-neg-in72.4%
metadata-eval72.4%
*-commutative72.4%
*-commutative72.4%
*-commutative72.4%
*-commutative72.4%
distribute-lft-neg-in72.4%
sin-neg72.4%
distribute-rgt-neg-in72.4%
metadata-eval72.4%
*-commutative72.4%
*-commutative72.4%
Simplified72.4%
sin-mult72.4%
div-inv72.4%
metadata-eval72.4%
*-commutative72.4%
div-inv72.4%
metadata-eval72.4%
*-commutative72.4%
cos-sum72.4%
cos-272.4%
div-inv72.4%
metadata-eval72.4%
*-commutative72.4%
Applied egg-rr72.4%
div-sub72.4%
+-inverses72.4%
cos-072.4%
metadata-eval72.4%
associate-*r*72.4%
metadata-eval72.4%
*-lft-identity72.4%
sub-neg72.4%
mul-1-neg72.4%
cos-neg72.4%
+-commutative72.4%
distribute-neg-in72.4%
mul-1-neg72.4%
remove-double-neg72.4%
sub-neg72.4%
Simplified72.4%
Taylor expanded in phi1 around 0 72.0%
Final simplification68.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (* phi1 0.5)))
(t_3 (cos (* phi1 0.5)))
(t_4
(-
1.0
(pow (- (* t_2 (cos (* phi2 0.5))) (* t_3 (sin (* phi2 0.5)))) 2.0)))
(t_5 (* t_1 (* t_0 t_0))))
(if (or (<= phi2 -2.65e-30) (not (<= phi2 1.75e+33)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma (cos (* -0.5 phi2)) t_2 (* (sin (* -0.5 phi2)) t_3)) 2.0)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt (+ t_4 (* t_1 (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_5 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- t_4 t_5))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin((phi1 * 0.5));
double t_3 = cos((phi1 * 0.5));
double t_4 = 1.0 - pow(((t_2 * cos((phi2 * 0.5))) - (t_3 * sin((phi2 * 0.5)))), 2.0);
double t_5 = t_1 * (t_0 * t_0);
double tmp;
if ((phi2 <= -2.65e-30) || !(phi2 <= 1.75e+33)) {
tmp = R * (2.0 * atan2(sqrt((pow(fma(cos((-0.5 * phi2)), t_2, (sin((-0.5 * phi2)) * t_3)), 2.0) + (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt((t_4 + (t_1 * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_5 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((t_4 - t_5))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(phi1 * 0.5)) t_3 = cos(Float64(phi1 * 0.5)) t_4 = Float64(1.0 - (Float64(Float64(t_2 * cos(Float64(phi2 * 0.5))) - Float64(t_3 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) t_5 = Float64(t_1 * Float64(t_0 * t_0)) tmp = 0.0 if ((phi2 <= -2.65e-30) || !(phi2 <= 1.75e+33)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(cos(Float64(-0.5 * phi2)), t_2, Float64(sin(Float64(-0.5 * phi2)) * t_3)) ^ 2.0) + Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64(t_4 + Float64(t_1 * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_5 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(t_4 - t_5))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(1.0 - N[Power[N[(N[(t$95$2 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$3 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -2.65e-30], N[Not[LessEqual[phi2, 1.75e+33]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$4 + N[(t$95$1 * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$5 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$4 - t$95$5), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_3 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_4 := 1 - {\left(t\_2 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_3 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_5 := t\_1 \cdot \left(t\_0 \cdot t\_0\right)\\
\mathbf{if}\;\phi_2 \leq -2.65 \cdot 10^{-30} \lor \neg \left(\phi_2 \leq 1.75 \cdot 10^{+33}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_2, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_3\right)\right)}^{2} + \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}{\sqrt{t\_4 + t\_1 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_5 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{t\_4 - t\_5}}\right)\\
\end{array}
\end{array}
if phi2 < -2.64999999999999987e-30 or 1.75000000000000005e33 < phi2 Initial program 46.6%
associate-*l*46.6%
Simplified46.6%
div-sub46.6%
sin-diff48.9%
div-inv48.9%
metadata-eval48.9%
div-inv48.9%
metadata-eval48.9%
div-inv48.9%
metadata-eval48.9%
div-inv48.9%
metadata-eval48.9%
Applied egg-rr48.9%
div-sub46.6%
sin-diff48.9%
div-inv48.9%
metadata-eval48.9%
div-inv48.9%
metadata-eval48.9%
div-inv48.9%
metadata-eval48.9%
div-inv48.9%
metadata-eval48.9%
Applied egg-rr77.8%
*-commutative77.8%
*-commutative77.8%
fma-neg77.8%
cos-neg77.8%
distribute-rgt-neg-in77.8%
metadata-eval77.8%
*-commutative77.8%
*-commutative77.8%
*-commutative77.8%
*-commutative77.8%
distribute-lft-neg-in77.8%
sin-neg77.8%
distribute-rgt-neg-in77.8%
metadata-eval77.8%
*-commutative77.8%
*-commutative77.8%
Simplified77.8%
sin-mult77.8%
div-inv77.8%
metadata-eval77.8%
*-commutative77.8%
div-inv77.8%
metadata-eval77.8%
*-commutative77.8%
cos-sum77.8%
cos-277.8%
div-inv77.8%
metadata-eval77.8%
*-commutative77.8%
Applied egg-rr77.8%
div-sub77.8%
+-inverses77.8%
cos-077.8%
metadata-eval77.8%
associate-*r*77.8%
metadata-eval77.8%
*-lft-identity77.8%
sub-neg77.8%
mul-1-neg77.8%
cos-neg77.8%
+-commutative77.8%
distribute-neg-in77.8%
mul-1-neg77.8%
remove-double-neg77.8%
sub-neg77.8%
Simplified77.8%
Taylor expanded in phi1 around 0 61.6%
if -2.64999999999999987e-30 < phi2 < 1.75000000000000005e33Initial program 74.4%
associate-*l*74.4%
Simplified74.4%
div-sub74.4%
sin-diff74.7%
div-inv74.7%
metadata-eval74.7%
div-inv74.7%
metadata-eval74.7%
div-inv74.7%
metadata-eval74.7%
div-inv74.7%
metadata-eval74.7%
Applied egg-rr74.7%
Final simplification68.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (cos (* phi1 0.5)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (sin (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* t_2 t_2))
(pow (+ (* (sin (* -0.5 phi2)) t_1) (* (cos (* -0.5 phi2)) t_3)) 2.0)))
(sqrt
(+
(-
1.0
(pow (- (* t_3 (cos (* phi2 0.5))) (* t_1 (sin (* phi2 0.5)))) 2.0))
(* t_0 (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = cos((phi1 * 0.5));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = sin((phi1 * 0.5));
return R * (2.0 * atan2(sqrt(((t_0 * (t_2 * t_2)) + pow(((sin((-0.5 * phi2)) * t_1) + (cos((-0.5 * phi2)) * t_3)), 2.0))), sqrt(((1.0 - pow(((t_3 * cos((phi2 * 0.5))) - (t_1 * sin((phi2 * 0.5)))), 2.0)) + (t_0 * ((cos((lambda2 - lambda1)) / 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
real(8) :: t_3
t_0 = cos(phi1) * cos(phi2)
t_1 = cos((phi1 * 0.5d0))
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = sin((phi1 * 0.5d0))
code = r * (2.0d0 * atan2(sqrt(((t_0 * (t_2 * t_2)) + (((sin(((-0.5d0) * phi2)) * t_1) + (cos(((-0.5d0) * phi2)) * t_3)) ** 2.0d0))), sqrt(((1.0d0 - (((t_3 * cos((phi2 * 0.5d0))) - (t_1 * sin((phi2 * 0.5d0)))) ** 2.0d0)) + (t_0 * ((cos((lambda2 - lambda1)) / 2.0d0) - 0.5d0))))))
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((phi1 * 0.5));
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = Math.sin((phi1 * 0.5));
return R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_2 * t_2)) + Math.pow(((Math.sin((-0.5 * phi2)) * t_1) + (Math.cos((-0.5 * phi2)) * t_3)), 2.0))), Math.sqrt(((1.0 - Math.pow(((t_3 * Math.cos((phi2 * 0.5))) - (t_1 * Math.sin((phi2 * 0.5)))), 2.0)) + (t_0 * ((Math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.cos((phi1 * 0.5)) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = math.sin((phi1 * 0.5)) return R * (2.0 * math.atan2(math.sqrt(((t_0 * (t_2 * t_2)) + math.pow(((math.sin((-0.5 * phi2)) * t_1) + (math.cos((-0.5 * phi2)) * t_3)), 2.0))), math.sqrt(((1.0 - math.pow(((t_3 * math.cos((phi2 * 0.5))) - (t_1 * math.sin((phi2 * 0.5)))), 2.0)) + (t_0 * ((math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = sin(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_2 * t_2)) + (Float64(Float64(sin(Float64(-0.5 * phi2)) * t_1) + Float64(cos(Float64(-0.5 * phi2)) * t_3)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_3 * cos(Float64(phi2 * 0.5))) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) + Float64(t_0 * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = cos((phi1 * 0.5)); t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = sin((phi1 * 0.5)); tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_2 * t_2)) + (((sin((-0.5 * phi2)) * t_1) + (cos((-0.5 * phi2)) * t_3)) ^ 2.0))), sqrt(((1.0 - (((t_3 * cos((phi2 * 0.5))) - (t_1 * sin((phi2 * 0.5)))) ^ 2.0)) + (t_0 * ((cos((lambda2 - lambda1)) / 2.0) - 0.5)))))); 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[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision] + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$3 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $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(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \sin \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_2 \cdot t\_2\right) + {\left(\sin \left(-0.5 \cdot \phi_2\right) \cdot t\_1 + \cos \left(-0.5 \cdot \phi_2\right) \cdot t\_3\right)}^{2}}}{\sqrt{\left(1 - {\left(t\_3 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) + t\_0 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 60.9%
associate-*l*61.0%
Simplified61.0%
div-sub61.0%
sin-diff62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
Applied egg-rr62.2%
div-sub61.0%
sin-diff62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
Applied egg-rr76.5%
*-commutative76.5%
*-commutative76.5%
fma-neg76.5%
cos-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
distribute-lft-neg-in76.5%
sin-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
*-commutative76.5%
Simplified76.5%
sin-mult76.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
cos-sum76.5%
cos-276.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
Applied egg-rr76.5%
div-sub76.5%
+-inverses76.5%
cos-076.5%
metadata-eval76.5%
associate-*r*76.5%
metadata-eval76.5%
*-lft-identity76.5%
sub-neg76.5%
mul-1-neg76.5%
cos-neg76.5%
+-commutative76.5%
distribute-neg-in76.5%
mul-1-neg76.5%
remove-double-neg76.5%
sub-neg76.5%
Simplified76.5%
fma-undefine76.5%
Applied egg-rr76.5%
Final simplification76.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(-
1.0
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))
t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * 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 - (((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * 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.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * 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.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * 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(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * 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[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 60.9%
associate-*l*61.0%
Simplified61.0%
div-sub61.0%
sin-diff62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
Applied egg-rr62.2%
Final simplification62.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(fma
(cos (* -0.5 phi2))
(sin (* phi1 0.5))
(* (sin (* -0.5 phi2)) (cos (* phi1 0.5))))
2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt
(-
1.0
(+
(pow (sin (- (* phi1 0.5) (* phi2 0.5))) 2.0)
(*
(cos phi2)
(* (cos phi1) (+ 0.5 (* -0.5 (cos (- lambda2 lambda1))))))))))))))
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((pow(fma(cos((-0.5 * phi2)), sin((phi1 * 0.5)), (sin((-0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - (pow(sin(((phi1 * 0.5) - (phi2 * 0.5))), 2.0) + (cos(phi2) * (cos(phi1) * (0.5 + (-0.5 * cos((lambda2 - lambda1)))))))))));
}
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((fma(cos(Float64(-0.5 * phi2)), sin(Float64(phi1 * 0.5)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 * 0.5) - Float64(phi2 * 0.5))) ^ 2.0) + Float64(cos(phi2) * Float64(cos(phi1) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda2 - lambda1)))))))))))) 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[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 * 0.5), $MachinePrecision] - N[(phi2 * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), \sin \left(\phi_1 \cdot 0.5\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{1 - \left({\sin \left(\phi_1 \cdot 0.5 - \phi_2 \cdot 0.5\right)}^{2} + \cos \phi_2 \cdot \left(\cos \phi_1 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_2 - \lambda_1\right)\right)\right)\right)}}\right)
\end{array}
\end{array}
Initial program 60.9%
associate-*l*61.0%
Simplified61.0%
div-sub61.0%
sin-diff62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
Applied egg-rr62.2%
div-sub61.0%
sin-diff62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
Applied egg-rr76.5%
*-commutative76.5%
*-commutative76.5%
fma-neg76.5%
cos-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
distribute-lft-neg-in76.5%
sin-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
*-commutative76.5%
Simplified76.5%
sin-mult76.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
cos-sum76.5%
cos-276.5%
div-inv76.5%
metadata-eval76.5%
*-commutative76.5%
Applied egg-rr76.5%
div-sub76.5%
+-inverses76.5%
cos-076.5%
metadata-eval76.5%
associate-*r*76.5%
metadata-eval76.5%
*-lft-identity76.5%
sub-neg76.5%
mul-1-neg76.5%
cos-neg76.5%
+-commutative76.5%
distribute-neg-in76.5%
mul-1-neg76.5%
remove-double-neg76.5%
sub-neg76.5%
Simplified76.5%
sub-neg76.5%
sin-diff61.8%
*-commutative61.8%
associate-*l*61.8%
div-inv61.8%
metadata-eval61.8%
Applied egg-rr61.8%
sub-neg61.8%
associate--l-61.8%
*-commutative61.8%
*-commutative61.8%
associate-*l*61.8%
*-commutative61.8%
*-commutative61.8%
sub-neg61.8%
*-commutative61.8%
distribute-rgt-neg-in61.8%
metadata-eval61.8%
Simplified61.8%
Final simplification61.8%
(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 (- phi1 phi2))) 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 * (phi1 - phi2))), 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(phi1 - phi2))) ^ 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[(phi1 - phi2), $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_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 60.9%
associate-*l*61.0%
Simplified61.0%
Applied egg-rr61.4%
unpow1/261.4%
unpow261.4%
rem-sqrt-square61.4%
*-commutative61.4%
Simplified61.4%
Final simplification61.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(+
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))
(* 2.0 (* R (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (phi1 - phi2))), 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)));
return 2.0 * (R * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0) + (cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))
code = 2.0d0 * (r * atan2(sqrt(t_0), sqrt((1.0d0 - t_0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0) + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)));
return 2.0 * (R * Math.atan2(Math.sqrt(t_0), Math.sqrt((1.0 - t_0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0) + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) return 2.0 * (R * math.atan2(math.sqrt(t_0), math.sqrt((1.0 - t_0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))) return Float64(2.0 * Float64(R * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = (sin((0.5 * (phi1 - phi2))) ^ 2.0) + (cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))); tmp = 2.0 * (R * atan2(sqrt(t_0), sqrt((1.0 - t_0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(2.0 * N[(R * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $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)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\\
2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 60.9%
associate-*r*60.9%
*-commutative60.9%
Simplified61.0%
Taylor expanded in phi1 around 0 61.0%
Final simplification61.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (cos phi1) (cos phi2)) (* t_1 t_1))))
(if (or (<= phi1 -760000000.0) (not (<= phi1 0.0003)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) t_0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(- 1.0 (+ (* (cos phi2) t_0) (pow (sin (* -0.5 phi2)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1);
double tmp;
if ((phi1 <= -760000000.0) || !(phi1 <= 0.0003)) {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin((phi1 / 2.0)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - ((cos(phi2) * t_0) + pow(sin((-0.5 * phi2)), 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((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1)
if ((phi1 <= (-760000000.0d0)) .or. (.not. (phi1 <= 0.0003d0))) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin((phi1 / 2.0d0)) ** 2.0d0))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (cos(phi1) * t_0)))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - ((cos(phi2) * t_0) + (sin(((-0.5d0) * phi2)) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = (Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1);
double tmp;
if ((phi1 <= -760000000.0) || !(phi1 <= 0.0003)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin((phi1 / 2.0)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (Math.cos(phi1) * t_0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - ((Math.cos(phi2) * t_0) + Math.pow(Math.sin((-0.5 * phi2)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = (math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1) tmp = 0 if (phi1 <= -760000000.0) or not (phi1 <= 0.0003): tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin((phi1 / 2.0)), 2.0))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (math.cos(phi1) * t_0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - ((math.cos(phi2) * t_0) + math.pow(math.sin((-0.5 * phi2)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) tmp = 0.0 if ((phi1 <= -760000000.0) || !(phi1 <= 0.0003)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_0) + (sin(Float64(-0.5 * phi2)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1); tmp = 0.0; if ((phi1 <= -760000000.0) || ~((phi1 <= 0.0003))) tmp = R * (2.0 * atan2(sqrt((t_2 + (sin((phi1 / 2.0)) ^ 2.0))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (cos(phi1) * t_0))))); else tmp = R * (2.0 * atan2(sqrt((t_2 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - ((cos(phi2) * t_0) + (sin((-0.5 * phi2)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi1, -760000000.0], N[Not[LessEqual[phi1, 0.0003]], $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[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 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)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)\\
\mathbf{if}\;\phi_1 \leq -760000000 \lor \neg \left(\phi_1 \leq 0.0003\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_0 + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -7.6e8 or 2.99999999999999974e-4 < phi1 Initial program 48.2%
associate-*l*48.3%
Simplified48.3%
Taylor expanded in phi2 around 0 48.3%
unpow248.3%
1-sub-sin48.3%
unpow248.3%
*-commutative48.3%
Simplified48.3%
Taylor expanded in phi1 around inf 48.9%
Taylor expanded in phi2 around 0 49.8%
*-commutative63.2%
Simplified49.8%
if -7.6e8 < phi1 < 2.99999999999999974e-4Initial program 72.2%
associate-*l*72.2%
Simplified72.2%
Taylor expanded in phi1 around 0 72.2%
Final simplification61.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -2550.0) (not (<= phi2 0.0026)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) t_0) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0))
(pow (sin (* phi2 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_1 t_1))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) t_0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -2550.0) || !(phi2 <= 0.0026)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - ((cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0)) + pow(sin((phi2 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_1 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * t_0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
if ((phi2 <= (-2550.0d0)) .or. (.not. (phi2 <= 0.0026d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * t_0) + (sin(((-0.5d0) * phi2)) ** 2.0d0))), sqrt((1.0d0 - ((cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 2.0d0)) + (sin((phi2 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_1 * t_1)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (cos(phi1) * t_0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -2550.0) || !(phi2 <= 0.0026)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * t_0) + Math.pow(Math.sin((-0.5 * phi2)), 2.0))), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0)) + Math.pow(Math.sin((phi2 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (Math.cos(phi1) * t_0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (phi2 <= -2550.0) or not (phi2 <= 0.0026): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * t_0) + math.pow(math.sin((-0.5 * phi2)), 2.0))), math.sqrt((1.0 - ((math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0)) + math.pow(math.sin((phi2 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (math.cos(phi1) * t_0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -2550.0) || !(phi2 <= 0.0026)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0)) + (sin(Float64(phi2 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((phi2 <= -2550.0) || ~((phi2 <= 0.0026))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + (sin((-0.5 * phi2)) ^ 2.0))), sqrt((1.0 - ((cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0)) + (sin((phi2 * 0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_1 * t_1)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (cos(phi1) * t_0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -2550.0], N[Not[LessEqual[phi2, 0.0026]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$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[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$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)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -2550 \lor \neg \left(\phi_2 \leq 0.0026\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2} + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t\_0}}\right)\\
\end{array}
\end{array}
if phi2 < -2550 or 0.0025999999999999999 < phi2 Initial program 47.0%
associate-*l*47.0%
Simplified47.0%
div-sub47.0%
sin-diff49.6%
div-inv49.6%
metadata-eval49.6%
div-inv49.6%
metadata-eval49.6%
div-inv49.6%
metadata-eval49.6%
div-inv49.6%
metadata-eval49.6%
Applied egg-rr49.6%
Taylor expanded in lambda1 around 0 42.1%
Taylor expanded in phi1 around 0 42.9%
Taylor expanded in phi1 around 0 41.4%
if -2550 < phi2 < 0.0025999999999999999Initial program 72.9%
associate-*l*72.9%
Simplified72.9%
Taylor expanded in phi2 around 0 72.9%
unpow272.9%
1-sub-sin73.0%
unpow273.0%
*-commutative73.0%
Simplified73.0%
Taylor expanded in phi2 around 0 73.0%
*-commutative73.0%
Simplified73.0%
Final simplification58.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -1.2e-16) (not (<= phi2 0.00021)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) t_0) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0))
(pow (sin (* phi2 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt
(-
(pow (cos (* phi1 0.5)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_1 t_1))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -1.2e-16) || !(phi2 <= 0.00021)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - ((cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0)) + pow(sin((phi2 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - ((cos(phi1) * cos(phi2)) * (t_1 * t_1))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
if ((phi2 <= (-1.2d-16)) .or. (.not. (phi2 <= 0.00021d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * t_0) + (sin(((-0.5d0) * phi2)) ** 2.0d0))), sqrt((1.0d0 - ((cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 2.0d0)) + (sin((phi2 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * t_0) + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - ((cos(phi1) * cos(phi2)) * (t_1 * t_1))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -1.2e-16) || !(phi2 <= 0.00021)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * t_0) + Math.pow(Math.sin((-0.5 * phi2)), 2.0))), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0)) + Math.pow(Math.sin((phi2 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * t_0) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - ((Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (phi2 <= -1.2e-16) or not (phi2 <= 0.00021): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * t_0) + math.pow(math.sin((-0.5 * phi2)), 2.0))), math.sqrt((1.0 - ((math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0)) + math.pow(math.sin((phi2 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * t_0) + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - ((math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -1.2e-16) || !(phi2 <= 0.00021)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0)) + (sin(Float64(phi2 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((phi2 <= -1.2e-16) || ~((phi2 <= 0.00021))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + (sin((-0.5 * phi2)) ^ 2.0))), sqrt((1.0 - ((cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0)) + (sin((phi2 * 0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_0) + (sin((phi1 * 0.5)) ^ 2.0))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - ((cos(phi1) * cos(phi2)) * (t_1 * t_1)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -1.2e-16], N[Not[LessEqual[phi2, 0.00021]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $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)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -1.2 \cdot 10^{-16} \lor \neg \left(\phi_2 \leq 0.00021\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2} + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -1.20000000000000002e-16 or 2.1000000000000001e-4 < phi2 Initial program 46.6%
associate-*l*46.6%
Simplified46.6%
div-sub46.6%
sin-diff49.1%
div-inv49.1%
metadata-eval49.1%
div-inv49.1%
metadata-eval49.1%
div-inv49.1%
metadata-eval49.1%
div-inv49.1%
metadata-eval49.1%
Applied egg-rr49.1%
Taylor expanded in lambda1 around 0 42.1%
Taylor expanded in phi1 around 0 42.4%
Taylor expanded in phi1 around 0 40.9%
if -1.20000000000000002e-16 < phi2 < 2.1000000000000001e-4Initial program 74.9%
associate-*l*74.9%
Simplified74.9%
Taylor expanded in phi2 around 0 74.9%
unpow274.9%
1-sub-sin75.0%
unpow275.0%
*-commutative75.0%
Simplified75.0%
Taylor expanded in phi2 around 0 75.0%
Final simplification58.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_0)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(* t_1 (+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)) - (t_1 * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)) - (t_1 * (0.5d0 + ((-0.5d0) * cos((lambda1 - lambda2)))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt(((t_1 * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)) - (t_1 * (0.5 + (-0.5 * Math.cos((lambda1 - lambda2)))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt(((t_1 * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)) - (t_1 * (0.5 + (-0.5 * math.cos((lambda1 - lambda2)))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) - Float64(t_1 * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0)) - (t_1 * (0.5 + (-0.5 * cos((lambda1 - lambda2))))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) - t\_1 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)}}\right)
\end{array}
\end{array}
Initial program 60.9%
associate-*l*61.0%
Simplified61.0%
*-commutative61.0%
cancel-sign-sub-inv61.0%
div-inv61.0%
metadata-eval61.0%
Applied egg-rr61.0%
Final simplification61.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2)))))
(if (or (<= phi2 -9.5e-6) (not (<= phi2 6.5e-31)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) (pow t_0 2.0)) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0))
(pow (sin (* phi2 0.5)) 2.0)))))))
(*
(* R 2.0)
(atan2
(hypot
(sin (* 0.5 (- phi1 phi2)))
(* (sqrt (* (cos phi1) (cos phi2))) t_0))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* phi1 0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double tmp;
if ((phi2 <= -9.5e-6) || !(phi2 <= 6.5e-31)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(t_0, 2.0)) + pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - ((cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0)) + pow(sin((phi2 * 0.5)), 2.0))))));
} else {
tmp = (R * 2.0) * atan2(hypot(sin((0.5 * (phi1 - phi2))), (sqrt((cos(phi1) * cos(phi2))) * t_0)), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((phi1 * 0.5)), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) tmp = 0.0 if ((phi2 <= -9.5e-6) || !(phi2 <= 6.5e-31)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (t_0 ^ 2.0)) + (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0)) + (sin(Float64(phi2 * 0.5)) ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(sqrt(Float64(cos(phi1) * cos(phi2))) * t_0)), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(phi1 * 0.5)) ^ 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]}, If[Or[LessEqual[phi2, -9.5e-6], N[Not[LessEqual[phi2, 6.5e-31]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * t$95$0), $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[(phi1 * 0.5), $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)\\
\mathbf{if}\;\phi_2 \leq -9.5 \cdot 10^{-6} \lor \neg \left(\phi_2 \leq 6.5 \cdot 10^{-31}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {t\_0}^{2} + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2} + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}\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{\cos \phi_1 \cdot \cos \phi_2} \cdot t\_0\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(\phi_1 \cdot 0.5\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -9.5000000000000005e-6 or 6.49999999999999967e-31 < phi2 Initial program 48.2%
associate-*l*48.2%
Simplified48.3%
div-sub48.3%
sin-diff50.7%
div-inv50.7%
metadata-eval50.7%
div-inv50.7%
metadata-eval50.7%
div-inv50.7%
metadata-eval50.7%
div-inv50.7%
metadata-eval50.7%
Applied egg-rr50.7%
Taylor expanded in lambda1 around 0 43.2%
Taylor expanded in phi1 around 0 41.9%
Taylor expanded in phi1 around 0 40.4%
if -9.5000000000000005e-6 < phi2 < 6.49999999999999967e-31Initial program 73.5%
associate-*r*73.5%
*-commutative73.5%
Simplified73.5%
Applied egg-rr61.3%
*-lft-identity61.3%
*-commutative61.3%
*-commutative61.3%
*-commutative61.3%
Simplified61.3%
Taylor expanded in phi2 around 0 61.3%
Final simplification50.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2)))))
(if (or (<= phi2 -7.5e-24) (not (<= phi2 6.5e-31)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) (pow t_0 2.0)) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0))
(pow (sin (* phi2 0.5)) 2.0)))))))
(*
(* R 2.0)
(atan2
(hypot (sin (* phi1 0.5)) (* 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 tmp;
if ((phi2 <= -7.5e-24) || !(phi2 <= 6.5e-31)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(t_0, 2.0)) + pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - ((cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0)) + pow(sin((phi2 * 0.5)), 2.0))))));
} else {
tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), (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))) tmp = 0.0 if ((phi2 <= -7.5e-24) || !(phi2 <= 6.5e-31)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (t_0 ^ 2.0)) + (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0)) + (sin(Float64(phi2 * 0.5)) ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), 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]}, If[Or[LessEqual[phi2, -7.5e-24], N[Not[LessEqual[phi2, 6.5e-31]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $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)\\
\mathbf{if}\;\phi_2 \leq -7.5 \cdot 10^{-24} \lor \neg \left(\phi_2 \leq 6.5 \cdot 10^{-31}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {t\_0}^{2} + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2} + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\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 < -7.50000000000000007e-24 or 6.49999999999999967e-31 < phi2 Initial program 48.9%
associate-*l*49.0%
Simplified49.0%
div-sub49.0%
sin-diff51.3%
div-inv51.3%
metadata-eval51.3%
div-inv51.3%
metadata-eval51.3%
div-inv51.3%
metadata-eval51.3%
div-inv51.3%
metadata-eval51.3%
Applied egg-rr51.3%
Taylor expanded in lambda1 around 0 44.1%
Taylor expanded in phi1 around 0 41.9%
Taylor expanded in phi1 around 0 40.5%
if -7.50000000000000007e-24 < phi2 < 6.49999999999999967e-31Initial program 73.7%
associate-*r*73.7%
*-commutative73.7%
Simplified73.7%
Applied egg-rr61.8%
*-lft-identity61.8%
*-commutative61.8%
*-commutative61.8%
*-commutative61.8%
Simplified61.8%
Taylor expanded in phi2 around 0 61.1%
Taylor expanded in phi2 around 0 61.1%
Final simplification50.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -2550.0) (not (<= phi2 0.00048)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0))
(pow (sin (* phi2 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_1 t_1))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -2550.0) || !(phi2 <= 0.00048)) {
tmp = R * (2.0 * atan2(sqrt((t_0 + pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - ((cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0)) + pow(sin((phi2 * 0.5)), 2.0))))));
} else {
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 - t_0))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
if ((phi2 <= (-2550.0d0)) .or. (.not. (phi2 <= 0.00048d0))) then
tmp = r * (2.0d0 * atan2(sqrt((t_0 + (sin(((-0.5d0) * phi2)) ** 2.0d0))), sqrt((1.0d0 - ((cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 2.0d0)) + (sin((phi2 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_1 * t_1)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - t_0))))
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) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -2550.0) || !(phi2 <= 0.00048)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + Math.pow(Math.sin((-0.5 * phi2)), 2.0))), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0)) + Math.pow(Math.sin((phi2 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - t_0))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (phi2 <= -2550.0) or not (phi2 <= 0.00048): tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + math.pow(math.sin((-0.5 * phi2)), 2.0))), math.sqrt((1.0 - ((math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0)) + math.pow(math.sin((phi2 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - t_0)))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -2550.0) || !(phi2 <= 0.00048)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0)) + (sin(Float64(phi2 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - t_0))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0); t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((phi2 <= -2550.0) || ~((phi2 <= 0.00048))) tmp = R * (2.0 * atan2(sqrt((t_0 + (sin((-0.5 * phi2)) ^ 2.0))), sqrt((1.0 - ((cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0)) + (sin((phi2 * 0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_1 * t_1)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - t_0)))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -2550.0], N[Not[LessEqual[phi2, 0.00048]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$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 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -2550 \lor \neg \left(\phi_2 \leq 0.00048\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2} + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - t\_0}}\right)\\
\end{array}
\end{array}
if phi2 < -2550 or 4.80000000000000012e-4 < phi2 Initial program 47.0%
associate-*l*47.0%
Simplified47.0%
div-sub47.0%
sin-diff49.6%
div-inv49.6%
metadata-eval49.6%
div-inv49.6%
metadata-eval49.6%
div-inv49.6%
metadata-eval49.6%
div-inv49.6%
metadata-eval49.6%
Applied egg-rr49.6%
Taylor expanded in lambda1 around 0 42.1%
Taylor expanded in phi1 around 0 42.9%
Taylor expanded in phi1 around 0 41.4%
if -2550 < phi2 < 4.80000000000000012e-4Initial program 72.9%
associate-*l*72.9%
Simplified72.9%
Taylor expanded in phi2 around 0 72.9%
unpow272.9%
1-sub-sin73.0%
unpow273.0%
*-commutative73.0%
Simplified73.0%
Taylor expanded in phi1 around 0 47.9%
*-commutative47.9%
Simplified47.9%
Final simplification44.9%
(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
(- 1.0 (* (cos phi2) (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(phi2) * 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(phi2) * (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(phi2) * 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(phi2) * 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(phi2) * (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(phi2) * (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[phi2], $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_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 60.9%
associate-*l*61.0%
Simplified61.0%
Taylor expanded in phi2 around 0 48.5%
unpow248.5%
1-sub-sin48.5%
unpow248.5%
*-commutative48.5%
Simplified48.5%
Taylor expanded in phi1 around 0 35.3%
*-commutative35.3%
Simplified35.3%
Final simplification35.3%
(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 2.0)) 2.0)))
(sqrt
(- 1.0 (* (cos phi2) (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 / 2.0)), 2.0))), sqrt((1.0 - (cos(phi2) * 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 / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (cos(phi2) * (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 / 2.0)), 2.0))), Math.sqrt((1.0 - (Math.cos(phi2) * 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 / 2.0)), 2.0))), math.sqrt((1.0 - (math.cos(phi2) * 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(phi1 / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(cos(phi2) * (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 / 2.0)) ^ 2.0))), sqrt((1.0 - (cos(phi2) * (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[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $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}{2}\right)}^{2}}}{\sqrt{1 - \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 60.9%
associate-*l*61.0%
Simplified61.0%
Taylor expanded in phi2 around 0 48.5%
unpow248.5%
1-sub-sin48.5%
unpow248.5%
*-commutative48.5%
Simplified48.5%
Taylor expanded in phi1 around inf 45.1%
Taylor expanded in phi1 around 0 32.0%
*-commutative35.3%
Simplified32.0%
Final simplification32.0%
(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 60.9%
associate-*r*60.9%
*-commutative60.9%
Simplified61.0%
Applied egg-rr43.5%
*-lft-identity43.5%
*-commutative43.5%
*-commutative43.5%
*-commutative43.5%
Simplified43.5%
Taylor expanded in phi2 around 0 35.3%
Taylor expanded in phi1 around 0 16.2%
Taylor expanded in phi2 around 0 18.7%
Final simplification18.7%
(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 60.9%
associate-*r*60.9%
*-commutative60.9%
Simplified61.0%
Applied egg-rr43.5%
*-lft-identity43.5%
*-commutative43.5%
*-commutative43.5%
*-commutative43.5%
Simplified43.5%
Taylor expanded in phi2 around 0 35.3%
Taylor expanded in phi1 around 0 16.2%
Taylor expanded in phi2 around 0 18.6%
Final simplification18.6%
(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 60.9%
associate-*r*60.9%
*-commutative60.9%
Simplified61.0%
Applied egg-rr43.5%
*-lft-identity43.5%
*-commutative43.5%
*-commutative43.5%
*-commutative43.5%
Simplified43.5%
Taylor expanded in phi2 around 0 35.3%
Taylor expanded in phi1 around 0 16.2%
Taylor expanded in phi2 around 0 17.9%
Final simplification17.9%
herbie shell --seed 2024145
(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))))))))))