
(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 18 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 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_2 (* t_2 (* (cos phi1) (cos phi2))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (- (* (cos (* 0.5 phi2)) t_0) (* (sin (* 0.5 phi2)) t_1)) 2.0)
t_3))
(sqrt
(-
1.0
(+
t_3
(pow
(fma (cos (* phi2 -0.5)) t_0 (* (sin (* phi2 -0.5)) t_1))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * (t_2 * (cos(phi1) * cos(phi2)));
return R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_1)), 2.0) + t_3)), sqrt((1.0 - (t_3 + pow(fma(cos((phi2 * -0.5)), t_0, (sin((phi2 * -0.5)) * t_1)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_2 * Float64(t_2 * Float64(cos(phi1) * cos(phi2)))) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(cos(Float64(0.5 * phi2)) * t_0) - Float64(sin(Float64(0.5 * phi2)) * t_1)) ^ 2.0) + t_3)), sqrt(Float64(1.0 - Float64(t_3 + (fma(cos(Float64(phi2 * -0.5)), t_0, Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 * N[(t$95$2 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 + N[Power[N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $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 := t_2 \cdot \left(t_2 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t_0 - \sin \left(0.5 \cdot \phi_2\right) \cdot t_1\right)}^{2} + t_3}}{\sqrt{1 - \left(t_3 + {\left(\mathsf{fma}\left(\cos \left(\phi_2 \cdot -0.5\right), t_0, \sin \left(\phi_2 \cdot -0.5\right) \cdot t_1\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.8%
div-sub65.8%
sin-diff66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
Applied egg-rr66.8%
div-sub65.8%
sin-diff66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
Applied egg-rr83.4%
*-commutative83.4%
*-commutative83.4%
fma-neg83.5%
cos-neg83.5%
*-commutative83.5%
distribute-rgt-neg-out83.5%
mul-1-neg83.5%
associate-*r*83.5%
metadata-eval83.5%
*-commutative83.5%
*-commutative83.5%
distribute-lft-neg-in83.5%
Simplified83.5%
Final simplification83.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0)
(* t_0 (* t_0 (* (cos phi1) (cos phi2)))))))
(* 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(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2))));
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 = (((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2))))
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.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.sin((0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0) + (t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2))));
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.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.sin((0.5 * phi2)) * math.cos((phi1 * 0.5)))), 2.0) + (t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2)))) 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((Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0) + Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2))))) 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 = (((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2)))); 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[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $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[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $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 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \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)}^{2} + t_0 \cdot \left(t_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_1}}{\sqrt{1 - t_1}}\right)
\end{array}
\end{array}
Initial program 65.8%
div-sub65.8%
sin-diff66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
Applied egg-rr66.8%
div-sub65.8%
sin-diff66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
Applied egg-rr83.4%
Final simplification83.4%
(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))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (- (* (cos (* 0.5 phi2)) t_0) (* (sin (* 0.5 phi2)) t_1)) 2.0)
(* t_2 (* t_2 (* (cos phi1) (cos phi2))))))
(sqrt
(-
1.0
(+
(*
(cos phi2)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(pow
(+ (* (cos (* phi2 -0.5)) t_0) (* (sin (* phi2 -0.5)) t_1))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_1)), 2.0) + (t_2 * (t_2 * (cos(phi1) * cos(phi2)))))), sqrt((1.0 - ((cos(phi2) * (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))) + pow(((cos((phi2 * -0.5)) * t_0) + (sin((phi2 * -0.5)) * t_1)), 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
real(8) :: t_1
real(8) :: t_2
t_0 = sin((phi1 * 0.5d0))
t_1 = cos((phi1 * 0.5d0))
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((((cos((0.5d0 * phi2)) * t_0) - (sin((0.5d0 * phi2)) * t_1)) ** 2.0d0) + (t_2 * (t_2 * (cos(phi1) * cos(phi2)))))), sqrt((1.0d0 - ((cos(phi2) * (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))) + (((cos((phi2 * (-0.5d0))) * t_0) + (sin((phi2 * (-0.5d0))) * t_1)) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((phi1 * 0.5));
double t_1 = Math.cos((phi1 * 0.5));
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.cos((0.5 * phi2)) * t_0) - (Math.sin((0.5 * phi2)) * t_1)), 2.0) + (t_2 * (t_2 * (Math.cos(phi1) * Math.cos(phi2)))))), Math.sqrt((1.0 - ((Math.cos(phi2) * (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + Math.pow(((Math.cos((phi2 * -0.5)) * t_0) + (Math.sin((phi2 * -0.5)) * t_1)), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((phi1 * 0.5)) t_1 = math.cos((phi1 * 0.5)) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.cos((0.5 * phi2)) * t_0) - (math.sin((0.5 * phi2)) * t_1)), 2.0) + (t_2 * (t_2 * (math.cos(phi1) * math.cos(phi2)))))), math.sqrt((1.0 - ((math.cos(phi2) * (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + math.pow(((math.cos((phi2 * -0.5)) * t_0) + (math.sin((phi2 * -0.5)) * t_1)), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(cos(Float64(0.5 * phi2)) * t_0) - Float64(sin(Float64(0.5 * phi2)) * t_1)) ^ 2.0) + Float64(t_2 * Float64(t_2 * Float64(cos(phi1) * cos(phi2)))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) + (Float64(Float64(cos(Float64(phi2 * -0.5)) * t_0) + Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((phi1 * 0.5)); t_1 = cos((phi1 * 0.5)); t_2 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_1)) ^ 2.0) + (t_2 * (t_2 * (cos(phi1) * cos(phi2)))))), sqrt((1.0 - ((cos(phi2) * (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))) + (((cos((phi2 * -0.5)) * t_0) + (sin((phi2 * -0.5)) * t_1)) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$2 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $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)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t_0 - \sin \left(0.5 \cdot \phi_2\right) \cdot t_1\right)}^{2} + t_2 \cdot \left(t_2 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + {\left(\cos \left(\phi_2 \cdot -0.5\right) \cdot t_0 + \sin \left(\phi_2 \cdot -0.5\right) \cdot t_1\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.8%
div-sub65.8%
sin-diff66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
Applied egg-rr66.8%
div-sub65.8%
sin-diff66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
Applied egg-rr83.4%
*-commutative83.4%
*-commutative83.4%
fma-neg83.5%
cos-neg83.5%
*-commutative83.5%
distribute-rgt-neg-out83.5%
mul-1-neg83.5%
associate-*r*83.5%
metadata-eval83.5%
*-commutative83.5%
*-commutative83.5%
distribute-lft-neg-in83.5%
Simplified83.5%
Taylor expanded in phi2 around inf 83.4%
Final simplification83.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (cos (* phi1 0.5)))
(t_3
(pow (- (* (cos (* 0.5 phi2)) t_0) (* (sin (* 0.5 phi2)) t_2)) 2.0))
(t_4 (* t_1 (* t_1 (* (cos phi1) (cos phi2))))))
(if (<= lambda2 1400.0)
(*
R
(*
2.0
(atan2
(sqrt
(+
t_3
(*
(cos phi2)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(sqrt
(-
1.0
(+
(* (cos phi2) (* (cos phi1) (pow (sin (* 0.5 lambda1)) 2.0)))
(pow
(+ (* (cos (* phi2 -0.5)) t_0) (* (sin (* phi2 -0.5)) t_2))
2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_3 t_4))
(sqrt (- 1.0 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_4)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos((phi1 * 0.5));
double t_3 = pow(((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_2)), 2.0);
double t_4 = t_1 * (t_1 * (cos(phi1) * cos(phi2)));
double tmp;
if (lambda2 <= 1400.0) {
tmp = R * (2.0 * atan2(sqrt((t_3 + (cos(phi2) * (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))), sqrt((1.0 - ((cos(phi2) * (cos(phi1) * pow(sin((0.5 * lambda1)), 2.0))) + pow(((cos((phi2 * -0.5)) * t_0) + (sin((phi2 * -0.5)) * t_2)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_3 + t_4)), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_4)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = sin((phi1 * 0.5d0))
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = cos((phi1 * 0.5d0))
t_3 = ((cos((0.5d0 * phi2)) * t_0) - (sin((0.5d0 * phi2)) * t_2)) ** 2.0d0
t_4 = t_1 * (t_1 * (cos(phi1) * cos(phi2)))
if (lambda2 <= 1400.0d0) then
tmp = r * (2.0d0 * atan2(sqrt((t_3 + (cos(phi2) * (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))))), sqrt((1.0d0 - ((cos(phi2) * (cos(phi1) * (sin((0.5d0 * lambda1)) ** 2.0d0))) + (((cos((phi2 * (-0.5d0))) * t_0) + (sin((phi2 * (-0.5d0))) * t_2)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_3 + t_4)), sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_4)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((phi1 * 0.5));
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.cos((phi1 * 0.5));
double t_3 = Math.pow(((Math.cos((0.5 * phi2)) * t_0) - (Math.sin((0.5 * phi2)) * t_2)), 2.0);
double t_4 = t_1 * (t_1 * (Math.cos(phi1) * Math.cos(phi2)));
double tmp;
if (lambda2 <= 1400.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + (Math.cos(phi2) * (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))))), Math.sqrt((1.0 - ((Math.cos(phi2) * (Math.cos(phi1) * Math.pow(Math.sin((0.5 * lambda1)), 2.0))) + Math.pow(((Math.cos((phi2 * -0.5)) * t_0) + (Math.sin((phi2 * -0.5)) * t_2)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + t_4)), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_4)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((phi1 * 0.5)) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.cos((phi1 * 0.5)) t_3 = math.pow(((math.cos((0.5 * phi2)) * t_0) - (math.sin((0.5 * phi2)) * t_2)), 2.0) t_4 = t_1 * (t_1 * (math.cos(phi1) * math.cos(phi2))) tmp = 0 if lambda2 <= 1400.0: tmp = R * (2.0 * math.atan2(math.sqrt((t_3 + (math.cos(phi2) * (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))), math.sqrt((1.0 - ((math.cos(phi2) * (math.cos(phi1) * math.pow(math.sin((0.5 * lambda1)), 2.0))) + math.pow(((math.cos((phi2 * -0.5)) * t_0) + (math.sin((phi2 * -0.5)) * t_2)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_3 + t_4)), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_4))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = cos(Float64(phi1 * 0.5)) t_3 = Float64(Float64(cos(Float64(0.5 * phi2)) * t_0) - Float64(sin(Float64(0.5 * phi2)) * t_2)) ^ 2.0 t_4 = Float64(t_1 * Float64(t_1 * Float64(cos(phi1) * cos(phi2)))) tmp = 0.0 if (lambda2 <= 1400.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + Float64(cos(phi2) * Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * Float64(cos(phi1) * (sin(Float64(0.5 * lambda1)) ^ 2.0))) + (Float64(Float64(cos(Float64(phi2 * -0.5)) * t_0) + Float64(sin(Float64(phi2 * -0.5)) * t_2)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + t_4)), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_4)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((phi1 * 0.5)); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = cos((phi1 * 0.5)); t_3 = ((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_2)) ^ 2.0; t_4 = t_1 * (t_1 * (cos(phi1) * cos(phi2))); tmp = 0.0; if (lambda2 <= 1400.0) tmp = R * (2.0 * atan2(sqrt((t_3 + (cos(phi2) * (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))), sqrt((1.0 - ((cos(phi2) * (cos(phi1) * (sin((0.5 * lambda1)) ^ 2.0))) + (((cos((phi2 * -0.5)) * t_0) + (sin((phi2 * -0.5)) * t_2)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((t_3 + t_4)), sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_4))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$1 * N[(t$95$1 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[lambda2, 1400.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_3 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t_0 - \sin \left(0.5 \cdot \phi_2\right) \cdot t_2\right)}^{2}\\
t_4 := t_1 \cdot \left(t_1 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
\mathbf{if}\;\lambda_2 \leq 1400:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_3 + \cos \phi_2 \cdot \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right) + {\left(\cos \left(\phi_2 \cdot -0.5\right) \cdot t_0 + \sin \left(\phi_2 \cdot -0.5\right) \cdot t_2\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_3 + t_4}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_4\right)}}\right)\\
\end{array}
\end{array}
if lambda2 < 1400Initial program 69.4%
div-sub69.4%
sin-diff70.3%
div-inv70.3%
metadata-eval70.3%
div-inv70.3%
metadata-eval70.3%
div-inv70.3%
metadata-eval70.3%
div-inv70.3%
metadata-eval70.3%
Applied egg-rr70.3%
div-sub69.4%
sin-diff70.3%
div-inv70.3%
metadata-eval70.3%
div-inv70.3%
metadata-eval70.3%
div-inv70.3%
metadata-eval70.3%
div-inv70.3%
metadata-eval70.3%
Applied egg-rr87.5%
*-commutative87.5%
*-commutative87.5%
fma-neg87.5%
cos-neg87.5%
*-commutative87.5%
distribute-rgt-neg-out87.5%
mul-1-neg87.5%
associate-*r*87.5%
metadata-eval87.5%
*-commutative87.5%
*-commutative87.5%
distribute-lft-neg-in87.5%
Simplified87.5%
Taylor expanded in phi1 around inf 87.5%
Taylor expanded in lambda2 around 0 74.2%
if 1400 < lambda2 Initial program 53.6%
div-sub53.6%
sin-diff54.5%
div-inv54.5%
metadata-eval54.5%
div-inv54.5%
metadata-eval54.5%
div-inv54.5%
metadata-eval54.5%
div-inv54.5%
metadata-eval54.5%
Applied egg-rr54.5%
Final simplification69.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2
(sqrt
(+
(pow (- (* (cos (* 0.5 phi2)) t_0) (* (sin (* 0.5 phi2)) t_1)) 2.0)
(*
(cos phi2)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))
(t_3
(pow
(+ (* (cos (* phi2 -0.5)) t_0) (* (sin (* phi2 -0.5)) t_1))
2.0)))
(if (<= lambda1 -12.0)
(*
R
(*
2.0
(atan2
t_2
(sqrt
(-
1.0
(+
(* (cos phi2) (* (cos phi1) (pow (sin (* 0.5 lambda1)) 2.0)))
t_3))))))
(*
R
(*
2.0
(atan2
t_2
(sqrt
(-
1.0
(+
(* (pow (sin (* lambda2 -0.5)) 2.0) (* (cos phi1) (cos phi2)))
t_3)))))))))
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 = sqrt((pow(((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_1)), 2.0) + (cos(phi2) * (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
double t_3 = pow(((cos((phi2 * -0.5)) * t_0) + (sin((phi2 * -0.5)) * t_1)), 2.0);
double tmp;
if (lambda1 <= -12.0) {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - ((cos(phi2) * (cos(phi1) * pow(sin((0.5 * lambda1)), 2.0))) + t_3)))));
} else {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - ((pow(sin((lambda2 * -0.5)), 2.0) * (cos(phi1) * cos(phi2))) + t_3)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: tmp
t_0 = sin((phi1 * 0.5d0))
t_1 = cos((phi1 * 0.5d0))
t_2 = sqrt(((((cos((0.5d0 * phi2)) * t_0) - (sin((0.5d0 * phi2)) * t_1)) ** 2.0d0) + (cos(phi2) * (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
t_3 = ((cos((phi2 * (-0.5d0))) * t_0) + (sin((phi2 * (-0.5d0))) * t_1)) ** 2.0d0
if (lambda1 <= (-12.0d0)) then
tmp = r * (2.0d0 * atan2(t_2, sqrt((1.0d0 - ((cos(phi2) * (cos(phi1) * (sin((0.5d0 * lambda1)) ** 2.0d0))) + t_3)))))
else
tmp = r * (2.0d0 * atan2(t_2, sqrt((1.0d0 - (((sin((lambda2 * (-0.5d0))) ** 2.0d0) * (cos(phi1) * cos(phi2))) + t_3)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((phi1 * 0.5));
double t_1 = Math.cos((phi1 * 0.5));
double t_2 = Math.sqrt((Math.pow(((Math.cos((0.5 * phi2)) * t_0) - (Math.sin((0.5 * phi2)) * t_1)), 2.0) + (Math.cos(phi2) * (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
double t_3 = Math.pow(((Math.cos((phi2 * -0.5)) * t_0) + (Math.sin((phi2 * -0.5)) * t_1)), 2.0);
double tmp;
if (lambda1 <= -12.0) {
tmp = R * (2.0 * Math.atan2(t_2, Math.sqrt((1.0 - ((Math.cos(phi2) * (Math.cos(phi1) * Math.pow(Math.sin((0.5 * lambda1)), 2.0))) + t_3)))));
} else {
tmp = R * (2.0 * Math.atan2(t_2, Math.sqrt((1.0 - ((Math.pow(Math.sin((lambda2 * -0.5)), 2.0) * (Math.cos(phi1) * Math.cos(phi2))) + t_3)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((phi1 * 0.5)) t_1 = math.cos((phi1 * 0.5)) t_2 = math.sqrt((math.pow(((math.cos((0.5 * phi2)) * t_0) - (math.sin((0.5 * phi2)) * t_1)), 2.0) + (math.cos(phi2) * (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) t_3 = math.pow(((math.cos((phi2 * -0.5)) * t_0) + (math.sin((phi2 * -0.5)) * t_1)), 2.0) tmp = 0 if lambda1 <= -12.0: tmp = R * (2.0 * math.atan2(t_2, math.sqrt((1.0 - ((math.cos(phi2) * (math.cos(phi1) * math.pow(math.sin((0.5 * lambda1)), 2.0))) + t_3))))) else: tmp = R * (2.0 * math.atan2(t_2, math.sqrt((1.0 - ((math.pow(math.sin((lambda2 * -0.5)), 2.0) * (math.cos(phi1) * math.cos(phi2))) + t_3))))) 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 = sqrt(Float64((Float64(Float64(cos(Float64(0.5 * phi2)) * t_0) - Float64(sin(Float64(0.5 * phi2)) * t_1)) ^ 2.0) + Float64(cos(phi2) * Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))) t_3 = Float64(Float64(cos(Float64(phi2 * -0.5)) * t_0) + Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0 tmp = 0.0 if (lambda1 <= -12.0) tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * Float64(cos(phi1) * (sin(Float64(0.5 * lambda1)) ^ 2.0))) + t_3)))))); else tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - Float64(Float64((sin(Float64(lambda2 * -0.5)) ^ 2.0) * Float64(cos(phi1) * cos(phi2))) + t_3)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((phi1 * 0.5)); t_1 = cos((phi1 * 0.5)); t_2 = sqrt(((((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_1)) ^ 2.0) + (cos(phi2) * (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); t_3 = ((cos((phi2 * -0.5)) * t_0) + (sin((phi2 * -0.5)) * t_1)) ^ 2.0; tmp = 0.0; if (lambda1 <= -12.0) tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - ((cos(phi2) * (cos(phi1) * (sin((0.5 * lambda1)) ^ 2.0))) + t_3))))); else tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - (((sin((lambda2 * -0.5)) ^ 2.0) * (cos(phi1) * cos(phi2))) + t_3))))); end tmp_2 = 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[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[(N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[lambda1, -12.0], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(N[(N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $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 := \sqrt{{\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t_0 - \sin \left(0.5 \cdot \phi_2\right) \cdot t_1\right)}^{2} + \cos \phi_2 \cdot \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}\\
t_3 := {\left(\cos \left(\phi_2 \cdot -0.5\right) \cdot t_0 + \sin \left(\phi_2 \cdot -0.5\right) \cdot t_1\right)}^{2}\\
\mathbf{if}\;\lambda_1 \leq -12:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_2}{\sqrt{1 - \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right) + t_3\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_2}{\sqrt{1 - \left({\sin \left(\lambda_2 \cdot -0.5\right)}^{2} \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right) + t_3\right)}}\right)\\
\end{array}
\end{array}
if lambda1 < -12Initial program 58.7%
div-sub58.7%
sin-diff59.4%
div-inv59.4%
metadata-eval59.4%
div-inv59.4%
metadata-eval59.4%
div-inv59.4%
metadata-eval59.4%
div-inv59.4%
metadata-eval59.4%
Applied egg-rr59.4%
div-sub58.7%
sin-diff59.4%
div-inv59.4%
metadata-eval59.4%
div-inv59.4%
metadata-eval59.4%
div-inv59.4%
metadata-eval59.4%
div-inv59.4%
metadata-eval59.4%
Applied egg-rr69.6%
*-commutative69.6%
*-commutative69.6%
fma-neg69.6%
cos-neg69.6%
*-commutative69.6%
distribute-rgt-neg-out69.6%
mul-1-neg69.6%
associate-*r*69.6%
metadata-eval69.6%
*-commutative69.6%
*-commutative69.6%
distribute-lft-neg-in69.6%
Simplified69.6%
Taylor expanded in phi1 around inf 69.5%
Taylor expanded in lambda2 around 0 69.5%
if -12 < lambda1 Initial program 68.0%
div-sub68.0%
sin-diff69.0%
div-inv69.0%
metadata-eval69.0%
div-inv69.0%
metadata-eval69.0%
div-inv69.0%
metadata-eval69.0%
div-inv69.0%
metadata-eval69.0%
Applied egg-rr69.0%
div-sub68.0%
sin-diff69.0%
div-inv69.0%
metadata-eval69.0%
div-inv69.0%
metadata-eval69.0%
div-inv69.0%
metadata-eval69.0%
div-inv69.0%
metadata-eval69.0%
Applied egg-rr87.6%
*-commutative87.6%
*-commutative87.6%
fma-neg87.6%
cos-neg87.6%
*-commutative87.6%
distribute-rgt-neg-out87.6%
mul-1-neg87.6%
associate-*r*87.6%
metadata-eval87.6%
*-commutative87.6%
*-commutative87.6%
distribute-lft-neg-in87.6%
Simplified87.6%
Taylor expanded in phi1 around inf 87.6%
Taylor expanded in lambda1 around 0 74.6%
Final simplification73.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2
(*
(cos phi2)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (- (* (cos (* 0.5 phi2)) t_0) (* (sin (* 0.5 phi2)) t_1)) 2.0)
t_2))
(sqrt
(-
1.0
(+
t_2
(pow
(+ (* (cos (* phi2 -0.5)) t_0) (* (sin (* phi2 -0.5)) t_1))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = cos(phi2) * (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_1)), 2.0) + t_2)), sqrt((1.0 - (t_2 + pow(((cos((phi2 * -0.5)) * t_0) + (sin((phi2 * -0.5)) * t_1)), 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
real(8) :: t_1
real(8) :: t_2
t_0 = sin((phi1 * 0.5d0))
t_1 = cos((phi1 * 0.5d0))
t_2 = cos(phi2) * (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((((cos((0.5d0 * phi2)) * t_0) - (sin((0.5d0 * phi2)) * t_1)) ** 2.0d0) + t_2)), sqrt((1.0d0 - (t_2 + (((cos((phi2 * (-0.5d0))) * t_0) + (sin((phi2 * (-0.5d0))) * t_1)) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((phi1 * 0.5));
double t_1 = Math.cos((phi1 * 0.5));
double t_2 = Math.cos(phi2) * (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.cos((0.5 * phi2)) * t_0) - (Math.sin((0.5 * phi2)) * t_1)), 2.0) + t_2)), Math.sqrt((1.0 - (t_2 + Math.pow(((Math.cos((phi2 * -0.5)) * t_0) + (Math.sin((phi2 * -0.5)) * t_1)), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((phi1 * 0.5)) t_1 = math.cos((phi1 * 0.5)) t_2 = math.cos(phi2) * (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.cos((0.5 * phi2)) * t_0) - (math.sin((0.5 * phi2)) * t_1)), 2.0) + t_2)), math.sqrt((1.0 - (t_2 + math.pow(((math.cos((phi2 * -0.5)) * t_0) + (math.sin((phi2 * -0.5)) * t_1)), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = Float64(cos(phi2) * Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(cos(Float64(0.5 * phi2)) * t_0) - Float64(sin(Float64(0.5 * phi2)) * t_1)) ^ 2.0) + t_2)), sqrt(Float64(1.0 - Float64(t_2 + (Float64(Float64(cos(Float64(phi2 * -0.5)) * t_0) + Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((phi1 * 0.5)); t_1 = cos((phi1 * 0.5)); t_2 = cos(phi2) * (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)); tmp = R * (2.0 * atan2(sqrt(((((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_1)) ^ 2.0) + t_2)), sqrt((1.0 - (t_2 + (((cos((phi2 * -0.5)) * t_0) + (sin((phi2 * -0.5)) * t_1)) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 + N[Power[N[(N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $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_2 \cdot \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t_0 - \sin \left(0.5 \cdot \phi_2\right) \cdot t_1\right)}^{2} + t_2}}{\sqrt{1 - \left(t_2 + {\left(\cos \left(\phi_2 \cdot -0.5\right) \cdot t_0 + \sin \left(\phi_2 \cdot -0.5\right) \cdot t_1\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.8%
div-sub65.8%
sin-diff66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
Applied egg-rr66.8%
div-sub65.8%
sin-diff66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
Applied egg-rr83.4%
*-commutative83.4%
*-commutative83.4%
fma-neg83.5%
cos-neg83.5%
*-commutative83.5%
distribute-rgt-neg-out83.5%
mul-1-neg83.5%
associate-*r*83.5%
metadata-eval83.5%
*-commutative83.5%
*-commutative83.5%
distribute-lft-neg-in83.5%
Simplified83.5%
Taylor expanded in phi1 around inf 83.5%
Taylor expanded in phi2 around inf 83.4%
Final simplification83.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* t_0 (* (cos phi1) (cos phi2))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0)
t_1))
(sqrt (- 1.0 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2)));
return R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + t_1)), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2)))
code = r * (2.0d0 * atan2(sqrt(((((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0) + t_1)), sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2)));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.sin((0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0) + t_1)), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2))) return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.sin((0.5 * phi2)) * math.cos((phi1 * 0.5)))), 2.0) + t_1)), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2)))) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2))); tmp = R * (2.0 * atan2(sqrt(((((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0) + t_1)), sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $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 := t_0 \cdot \left(t_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \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)}^{2} + t_1}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_1\right)}}\right)
\end{array}
\end{array}
Initial program 65.8%
div-sub65.8%
sin-diff66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
Applied egg-rr66.8%
Final simplification66.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0)
(*
(cos phi2)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* t_0 (* (cos phi1) (cos phi2))))))))))))
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(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + (cos(phi2) * (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2)))))))));
}
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((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0) + (cos(phi2) * (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))))), sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2)))))))))
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.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.sin((0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0) + (Math.cos(phi2) * (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))))), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2)))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.sin((0.5 * phi2)) * math.cos((phi1 * 0.5)))), 2.0) + (math.cos(phi2) * (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2)))))))))
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(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0) + Float64(cos(phi2) * Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2)))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0) + (cos(phi2) * (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))), sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2))))))))); 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[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $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[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $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(\cos \left(0.5 \cdot \phi_2\right) \cdot \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)}^{2} + \cos \phi_2 \cdot \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_0 \cdot \left(t_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\right)}}\right)
\end{array}
\end{array}
Initial program 65.8%
div-sub65.8%
sin-diff66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
div-inv66.8%
metadata-eval66.8%
Applied egg-rr66.8%
Taylor expanded in phi1 around inf 66.8%
Final simplification66.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* t_0 (* (cos phi1) (cos phi2))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt (- 1.0 (+ t_1 (- 0.5 (/ (cos (- phi1 phi2)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2)));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt((1.0 - (t_1 + (0.5 - (cos((phi1 - phi2)) / 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
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2)))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt((1.0d0 - (t_1 + (0.5d0 - (cos((phi1 - phi2)) / 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));
double t_1 = t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2)));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt((1.0 - (t_1 + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2))) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt((1.0 - (t_1 + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2)))) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(t_1 + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2))); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt((1.0 - (t_1 + (0.5 - (cos((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]}, Block[{t$95$1 = N[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t_0 \cdot \left(t_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_1}}{\sqrt{1 - \left(t_1 + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)\right)}}\right)
\end{array}
\end{array}
Initial program 65.8%
unpow265.8%
sin-mult65.9%
div-inv65.9%
metadata-eval65.9%
div-inv65.9%
metadata-eval65.9%
div-inv65.9%
metadata-eval65.9%
div-inv65.9%
metadata-eval65.9%
Applied egg-rr65.9%
div-sub65.9%
+-inverses65.9%
cos-065.9%
metadata-eval65.9%
distribute-lft-out65.9%
metadata-eval65.9%
*-rgt-identity65.9%
Simplified65.9%
Final simplification65.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))
(if (<= phi2 1.15e-17)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* t_0 (* (cos phi1) (cos phi2))))))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) t_1))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) 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((-0.5 * (lambda2 - lambda1))), 2.0);
double tmp;
if (phi2 <= 1.15e-17) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2)))))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * t_1)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * 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(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0
if (phi2 <= 1.15d-17) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2)))))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (cos(phi1) * t_1)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * 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.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0);
double tmp;
if (phi2 <= 1.15e-17) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2)))))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (Math.cos(phi1) * t_1)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * t_1)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0) tmp = 0 if phi2 <= 1.15e-17: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2)))))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (math.cos(phi1) * t_1))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi2 * -0.5)), 2.0) + (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * t_1))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 tmp = 0.0 if (phi2 <= 1.15e-17) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2)))))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_1)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin((-0.5 * (lambda2 - lambda1))) ^ 2.0; tmp = 0.0; if (phi2 <= 1.15e-17) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2)))))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (cos(phi1) * t_1))))); else tmp = R * (2.0 * atan2(sqrt(((sin((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * t_1))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi2, 1.15e-17], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $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$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq 1.15 \cdot 10^{-17}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_0 \cdot \left(t_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t_1}}\right)\\
\end{array}
\end{array}
if phi2 < 1.15000000000000004e-17Initial program 70.5%
Taylor expanded in phi2 around 0 61.3%
associate--r+61.3%
unpow261.3%
*-commutative61.3%
*-commutative61.3%
1-sub-sin61.3%
*-commutative61.3%
*-commutative61.3%
unpow261.3%
*-commutative61.3%
sub-neg61.3%
mul-1-neg61.3%
+-commutative61.3%
*-commutative61.3%
Simplified61.3%
if 1.15000000000000004e-17 < phi2 Initial program 53.4%
Taylor expanded in phi1 around 0 51.9%
associate--r+51.9%
unpow251.9%
1-sub-sin52.0%
unpow252.0%
*-commutative52.0%
sub-neg52.0%
mul-1-neg52.0%
+-commutative52.0%
*-commutative52.0%
distribute-lft-in52.0%
associate-*r*52.0%
metadata-eval52.0%
metadata-eval52.0%
associate-*r*52.0%
distribute-lft-in52.0%
+-commutative52.0%
Simplified52.0%
Taylor expanded in phi1 around 0 53.0%
Final simplification59.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= (- lambda1 lambda2) -2000000.0)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* t_0 (* (cos phi1) (cos phi2))))))
(sqrt (- 1.0 (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));
double tmp;
if ((lambda1 - lambda2) <= -2000000.0) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2)))))), sqrt((1.0 - pow(sin((0.5 * (phi1 - 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) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
if ((lambda1 - lambda2) <= (-2000000.0d0)) then
tmp = r * (2.0d0 * atan2(sqrt(((sin((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2)))))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - 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.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((lambda1 - lambda2) <= -2000000.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2)))))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (lambda1 - lambda2) <= -2000000.0: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi2 * -0.5)), 2.0) + (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2)))))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (Float64(lambda1 - lambda2) <= -2000000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2)))))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((lambda1 - lambda2) <= -2000000.0) tmp = R * (2.0 * atan2(sqrt(((sin((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2)))))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -2000000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -2000000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_0 \cdot \left(t_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -2e6Initial program 64.4%
Taylor expanded in phi1 around 0 50.1%
associate--r+50.1%
unpow250.1%
1-sub-sin50.1%
unpow250.1%
*-commutative50.1%
sub-neg50.1%
mul-1-neg50.1%
+-commutative50.1%
*-commutative50.1%
distribute-lft-in50.1%
associate-*r*50.1%
metadata-eval50.1%
metadata-eval50.1%
associate-*r*50.1%
distribute-lft-in50.1%
+-commutative50.1%
Simplified50.1%
Taylor expanded in phi1 around 0 50.5%
if -2e6 < (-.f64 lambda1 lambda2) Initial program 66.7%
Taylor expanded in lambda2 around 0 54.2%
Taylor expanded in lambda1 around 0 42.7%
Final simplification45.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= (- lambda1 lambda2) -2000000.0)
(*
R
(*
2.0
(atan2
(sqrt
(+ t_0 (* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* t_1 (* t_1 (* (cos phi1) (cos phi2))))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((lambda1 - lambda2) <= -2000000.0) {
tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_0 + (t_1 * (t_1 * (cos(phi1) * cos(phi2)))))), sqrt((1.0 - pow(sin((0.5 * (phi1 - 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) :: tmp
t_0 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
if ((lambda1 - lambda2) <= (-2000000.0d0)) then
tmp = r * (2.0d0 * atan2(sqrt((t_0 + (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_0 + (t_1 * (t_1 * (cos(phi1) * cos(phi2)))))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - 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(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((lambda1 - lambda2) <= -2000000.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + (t_1 * (t_1 * (Math.cos(phi1) * Math.cos(phi2)))))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (lambda1 - lambda2) <= -2000000.0: tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + (t_1 * (t_1 * (math.cos(phi1) * math.cos(phi2)))))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (Float64(lambda1 - lambda2) <= -2000000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(t_1 * Float64(t_1 * Float64(cos(phi1) * cos(phi2)))))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((lambda1 - lambda2) <= -2000000.0) tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))), sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); else tmp = R * (2.0 * atan2(sqrt((t_0 + (t_1 * (t_1 * (cos(phi1) * cos(phi2)))))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -2000000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(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]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(t$95$1 * N[(t$95$1 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -2000000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_0 + \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_0 + t_1 \cdot \left(t_1 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -2e6Initial program 64.4%
Taylor expanded in phi1 around 0 50.1%
associate--r+50.1%
unpow250.1%
1-sub-sin50.1%
unpow250.1%
*-commutative50.1%
sub-neg50.1%
mul-1-neg50.1%
+-commutative50.1%
*-commutative50.1%
distribute-lft-in50.1%
associate-*r*50.1%
metadata-eval50.1%
metadata-eval50.1%
associate-*r*50.1%
distribute-lft-in50.1%
+-commutative50.1%
Simplified50.1%
Taylor expanded in phi2 around 0 34.9%
Taylor expanded in phi1 around 0 34.9%
*-commutative34.9%
Simplified34.9%
if -2e6 < (-.f64 lambda1 lambda2) Initial program 66.7%
Taylor expanded in lambda2 around 0 54.2%
Taylor expanded in lambda1 around 0 42.7%
Final simplification39.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (<= phi2 0.38)
(*
R
(*
2.0
(atan2
(sqrt
(+ (* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)) t_0))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_0
(*
(* (sin (/ (- lambda1 lambda2) 2.0)) (* (cos phi1) (cos phi2)))
(sin (* lambda2 -0.5)))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (phi2 <= 0.38) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + t_0)), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_0 + ((sin(((lambda1 - lambda2) / 2.0)) * (cos(phi1) * cos(phi2))) * sin((lambda2 * -0.5))))), sqrt((1.0 - pow(sin((0.5 * (phi1 - 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) :: tmp
t_0 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
if (phi2 <= 0.38d0) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + t_0)), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_0 + ((sin(((lambda1 - lambda2) / 2.0d0)) * (cos(phi1) * cos(phi2))) * sin((lambda2 * (-0.5d0)))))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - 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(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (phi2 <= 0.38) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + t_0)), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + ((Math.sin(((lambda1 - lambda2) / 2.0)) * (Math.cos(phi1) * Math.cos(phi2))) * Math.sin((lambda2 * -0.5))))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) tmp = 0 if phi2 <= 0.38: tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + t_0)), math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + ((math.sin(((lambda1 - lambda2) / 2.0)) * (math.cos(phi1) * math.cos(phi2))) * math.sin((lambda2 * -0.5))))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if (phi2 <= 0.38) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + t_0)), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(Float64(sin(Float64(Float64(lambda1 - lambda2) / 2.0)) * Float64(cos(phi1) * cos(phi2))) * sin(Float64(lambda2 * -0.5))))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = 0.0; if (phi2 <= 0.38) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + t_0)), sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); else tmp = R * (2.0 * atan2(sqrt((t_0 + ((sin(((lambda1 - lambda2) / 2.0)) * (cos(phi1) * cos(phi2))) * sin((lambda2 * -0.5))))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi2, 0.38], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq 0.38:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + t_0}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_0 + \left(\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot \sin \left(\lambda_2 \cdot -0.5\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi2 < 0.38Initial program 70.8%
Taylor expanded in phi1 around 0 51.7%
associate--r+51.7%
unpow251.7%
1-sub-sin51.7%
unpow251.7%
*-commutative51.7%
sub-neg51.7%
mul-1-neg51.7%
+-commutative51.7%
*-commutative51.7%
distribute-lft-in51.7%
associate-*r*51.7%
metadata-eval51.7%
metadata-eval51.7%
associate-*r*51.7%
distribute-lft-in51.7%
+-commutative51.7%
Simplified51.7%
Taylor expanded in phi2 around 0 42.4%
Taylor expanded in phi2 around 0 42.5%
if 0.38 < phi2 Initial program 51.2%
Taylor expanded in lambda2 around 0 43.0%
Taylor expanded in lambda1 around 0 30.8%
Taylor expanded in lambda1 around 0 30.3%
Final simplification39.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(((cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $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[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
Initial program 65.8%
Taylor expanded in phi1 around 0 51.5%
associate--r+51.4%
unpow251.4%
1-sub-sin51.5%
unpow251.5%
*-commutative51.5%
sub-neg51.5%
mul-1-neg51.5%
+-commutative51.5%
*-commutative51.5%
distribute-lft-in51.5%
associate-*r*51.5%
metadata-eval51.5%
metadata-eval51.5%
associate-*r*51.5%
distribute-lft-in51.5%
+-commutative51.5%
Simplified51.5%
Taylor expanded in phi2 around 0 36.5%
Taylor expanded in phi2 around 0 36.7%
Final simplification36.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))), sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $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[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
Initial program 65.8%
Taylor expanded in phi1 around 0 51.5%
associate--r+51.4%
unpow251.4%
1-sub-sin51.5%
unpow251.5%
*-commutative51.5%
sub-neg51.5%
mul-1-neg51.5%
+-commutative51.5%
*-commutative51.5%
distribute-lft-in51.5%
associate-*r*51.5%
metadata-eval51.5%
metadata-eval51.5%
associate-*r*51.5%
distribute-lft-in51.5%
+-commutative51.5%
Simplified51.5%
Taylor expanded in phi2 around 0 36.5%
Taylor expanded in phi1 around 0 36.4%
*-commutative36.4%
Simplified36.4%
Final simplification36.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt(((sin((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi2 * -0.5)), 2.0) + (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((sin((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))), sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
Initial program 65.8%
Taylor expanded in phi1 around 0 51.5%
associate--r+51.4%
unpow251.4%
1-sub-sin51.5%
unpow251.5%
*-commutative51.5%
sub-neg51.5%
mul-1-neg51.5%
+-commutative51.5%
*-commutative51.5%
distribute-lft-in51.5%
associate-*r*51.5%
metadata-eval51.5%
metadata-eval51.5%
associate-*r*51.5%
distribute-lft-in51.5%
+-commutative51.5%
Simplified51.5%
Taylor expanded in phi2 around 0 36.5%
Taylor expanded in phi1 around 0 33.9%
Final simplification33.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2)))))
(*
R
(*
2.0
(atan2
t_0
(sqrt
(-
1.0
(+
(* (cos phi2) (* (cos phi1) (pow (sin (* 0.5 lambda1)) 2.0)))
(pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
return R * (2.0 * atan2(t_0, sqrt((1.0 - ((cos(phi2) * (cos(phi1) * pow(sin((0.5 * lambda1)), 2.0))) + pow(t_0, 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (phi1 - phi2)))
code = r * (2.0d0 * atan2(t_0, sqrt((1.0d0 - ((cos(phi2) * (cos(phi1) * (sin((0.5d0 * lambda1)) ** 2.0d0))) + (t_0 ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (phi1 - phi2)));
return R * (2.0 * Math.atan2(t_0, Math.sqrt((1.0 - ((Math.cos(phi2) * (Math.cos(phi1) * Math.pow(Math.sin((0.5 * lambda1)), 2.0))) + Math.pow(t_0, 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (phi1 - phi2))) return R * (2.0 * math.atan2(t_0, math.sqrt((1.0 - ((math.cos(phi2) * (math.cos(phi1) * math.pow(math.sin((0.5 * lambda1)), 2.0))) + math.pow(t_0, 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) return Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * Float64(cos(phi1) * (sin(Float64(0.5 * lambda1)) ^ 2.0))) + (t_0 ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))); tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - ((cos(phi2) * (cos(phi1) * (sin((0.5 * lambda1)) ^ 2.0))) + (t_0 ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_0}{\sqrt{1 - \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right) + {t_0}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.8%
Taylor expanded in lambda2 around 0 50.6%
Taylor expanded in lambda1 around 0 32.1%
Taylor expanded in lambda2 around 0 15.3%
Taylor expanded in lambda2 around 0 15.3%
Final simplification15.3%
(FPCore (R lambda1 lambda2 phi1 phi2) :precision binary64 (let* ((t_0 (sin (* 0.5 (- phi1 phi2))))) (* R (* 2.0 (atan2 t_0 (sqrt (- 1.0 (pow t_0 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
return R * (2.0 * atan2(t_0, sqrt((1.0 - pow(t_0, 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (phi1 - phi2)))
code = r * (2.0d0 * atan2(t_0, sqrt((1.0d0 - (t_0 ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (phi1 - phi2)));
return R * (2.0 * Math.atan2(t_0, Math.sqrt((1.0 - Math.pow(t_0, 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (phi1 - phi2))) return R * (2.0 * math.atan2(t_0, math.sqrt((1.0 - math.pow(t_0, 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) return Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - (t_0 ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))); tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - (t_0 ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_0}{\sqrt{1 - {t_0}^{2}}}\right)
\end{array}
\end{array}
Initial program 65.8%
Taylor expanded in lambda2 around 0 50.6%
Taylor expanded in lambda1 around 0 32.1%
Taylor expanded in lambda2 around 0 15.3%
Taylor expanded in lambda1 around 0 15.1%
Final simplification15.1%
herbie shell --seed 2023187
(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))))))))))