
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 29 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(*
2.0
(*
R
(atan2
(sqrt
(+
(*
(cos phi1)
(*
(cos phi2)
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0)))
t_0))
(sqrt
(-
1.0
(+
t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
return 2.0 * (R * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0))) + t_0)), sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = ((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
code = 2.0d0 * (r * atan2(sqrt(((cos(phi1) * (cos(phi2) * (((sin((lambda1 / 2.0d0)) * cos((lambda2 / 2.0d0))) - (cos((lambda1 / 2.0d0)) * sin((lambda2 / 2.0d0)))) ** 2.0d0))) + t_0)), sqrt((1.0d0 - (t_0 + (cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
return 2.0 * (R * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(((Math.sin((lambda1 / 2.0)) * Math.cos((lambda2 / 2.0))) - (Math.cos((lambda1 / 2.0)) * Math.sin((lambda2 / 2.0)))), 2.0))) + t_0)), Math.sqrt((1.0 - (t_0 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) return 2.0 * (R * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(((math.sin((lambda1 / 2.0)) * math.cos((lambda2 / 2.0))) - (math.cos((lambda1 / 2.0)) * math.sin((lambda2 / 2.0)))), 2.0))) + t_0)), math.sqrt((1.0 - (t_0 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 return Float64(2.0 * Float64(R * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0))) + t_0)), sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; tmp = 2.0 * (R * atan2(sqrt(((cos(phi1) * (cos(phi2) * (((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))) ^ 2.0))) + t_0)), sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(2.0 * N[(R * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right)}^{2}\right) + t\_0}}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
div-sub62.4%
sin-diff63.7%
Applied egg-rr63.7%
div-sub62.4%
sin-diff63.7%
Applied egg-rr82.6%
Taylor expanded in R around 0 82.5%
*-commutative82.5%
metadata-eval82.5%
div-inv82.5%
div-sub82.5%
sin-diff83.1%
Applied egg-rr83.1%
Final simplification83.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))
(t_3 (sqrt (- 1.0 (+ t_2 (* (cos phi1) (* (cos phi2) t_0))))))
(t_4
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_1 (* (* (cos phi1) (cos phi2)) t_1)))))
(if (<= (atan2 (sqrt t_4) (sqrt (- 1.0 t_4))) 0.04)
(* 2.0 (* R (atan2 (sqrt (+ t_2 (* (cos phi1) t_0))) t_3)))
(*
2.0
(*
R
(atan2
(sqrt
(+
t_2
(*
(cos phi1)
(* (cos phi2) (- 0.5 (/ (cos (- lambda1 lambda2)) 2.0))))))
t_3))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double t_3 = sqrt((1.0 - (t_2 + (cos(phi1) * (cos(phi2) * t_0)))));
double t_4 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * ((cos(phi1) * cos(phi2)) * t_1));
double tmp;
if (atan2(sqrt(t_4), sqrt((1.0 - t_4))) <= 0.04) {
tmp = 2.0 * (R * atan2(sqrt((t_2 + (cos(phi1) * t_0))), t_3));
} else {
tmp = 2.0 * (R * atan2(sqrt((t_2 + (cos(phi1) * (cos(phi2) * (0.5 - (cos((lambda1 - lambda2)) / 2.0)))))), t_3));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = ((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
t_3 = sqrt((1.0d0 - (t_2 + (cos(phi1) * (cos(phi2) * t_0)))))
t_4 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_1 * ((cos(phi1) * cos(phi2)) * t_1))
if (atan2(sqrt(t_4), sqrt((1.0d0 - t_4))) <= 0.04d0) then
tmp = 2.0d0 * (r * atan2(sqrt((t_2 + (cos(phi1) * t_0))), t_3))
else
tmp = 2.0d0 * (r * atan2(sqrt((t_2 + (cos(phi1) * (cos(phi2) * (0.5d0 - (cos((lambda1 - lambda2)) / 2.0d0)))))), t_3))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
double t_3 = Math.sqrt((1.0 - (t_2 + (Math.cos(phi1) * (Math.cos(phi2) * t_0)))));
double t_4 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * ((Math.cos(phi1) * Math.cos(phi2)) * t_1));
double tmp;
if (Math.atan2(Math.sqrt(t_4), Math.sqrt((1.0 - t_4))) <= 0.04) {
tmp = 2.0 * (R * Math.atan2(Math.sqrt((t_2 + (Math.cos(phi1) * t_0))), t_3));
} else {
tmp = 2.0 * (R * Math.atan2(Math.sqrt((t_2 + (Math.cos(phi1) * (Math.cos(phi2) * (0.5 - (Math.cos((lambda1 - lambda2)) / 2.0)))))), t_3));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) t_3 = math.sqrt((1.0 - (t_2 + (math.cos(phi1) * (math.cos(phi2) * t_0))))) t_4 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * ((math.cos(phi1) * math.cos(phi2)) * t_1)) tmp = 0 if math.atan2(math.sqrt(t_4), math.sqrt((1.0 - t_4))) <= 0.04: tmp = 2.0 * (R * math.atan2(math.sqrt((t_2 + (math.cos(phi1) * t_0))), t_3)) else: tmp = 2.0 * (R * math.atan2(math.sqrt((t_2 + (math.cos(phi1) * (math.cos(phi2) * (0.5 - (math.cos((lambda1 - lambda2)) / 2.0)))))), t_3)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_3 = sqrt(Float64(1.0 - Float64(t_2 + Float64(cos(phi1) * Float64(cos(phi2) * t_0))))) t_4 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1))) tmp = 0.0 if (atan(sqrt(t_4), sqrt(Float64(1.0 - t_4))) <= 0.04) tmp = Float64(2.0 * Float64(R * atan(sqrt(Float64(t_2 + Float64(cos(phi1) * t_0))), t_3))); else tmp = Float64(2.0 * Float64(R * atan(sqrt(Float64(t_2 + Float64(cos(phi1) * Float64(cos(phi2) * Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) / 2.0)))))), t_3))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = ((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; t_3 = sqrt((1.0 - (t_2 + (cos(phi1) * (cos(phi2) * t_0))))); t_4 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_1 * ((cos(phi1) * cos(phi2)) * t_1)); tmp = 0.0; if (atan2(sqrt(t_4), sqrt((1.0 - t_4))) <= 0.04) tmp = 2.0 * (R * atan2(sqrt((t_2 + (cos(phi1) * t_0))), t_3)); else tmp = 2.0 * (R * atan2(sqrt((t_2 + (cos(phi1) * (cos(phi2) * (0.5 - (cos((lambda1 - lambda2)) / 2.0)))))), t_3)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(1.0 - N[(t$95$2 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[ArcTan[N[Sqrt[t$95$4], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 0.04], N[(2.0 * N[(R * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(2.0 * N[(R * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_3 := \sqrt{1 - \left(t\_2 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot t\_0\right)\right)}\\
t_4 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right)\\
\mathbf{if}\;\tan^{-1}_* \frac{\sqrt{t\_4}}{\sqrt{1 - t\_4}} \leq 0.04:\\
\;\;\;\;2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + \cos \phi_1 \cdot t\_0}}{t\_3}\right)\\
\mathbf{else}:\\
\;\;\;\;2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}\right)\right)}}{t\_3}\right)\\
\end{array}
\end{array}
if (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) < 0.0400000000000000008Initial program 88.9%
div-sub88.9%
sin-diff89.1%
Applied egg-rr89.1%
div-sub88.9%
sin-diff89.1%
Applied egg-rr92.6%
Taylor expanded in R around 0 92.6%
Taylor expanded in phi2 around 0 92.6%
*-commutative92.6%
Simplified92.6%
if 0.0400000000000000008 < (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) Initial program 59.8%
div-sub59.8%
sin-diff61.2%
Applied egg-rr61.2%
div-sub59.8%
sin-diff61.2%
Applied egg-rr81.6%
Taylor expanded in R around 0 81.6%
*-commutative81.6%
metadata-eval81.6%
div-inv81.6%
pow281.6%
sin-mult81.6%
Applied egg-rr81.5%
div-sub81.6%
+-inverses81.6%
cos-081.6%
metadata-eval81.6%
associate-*r*81.6%
metadata-eval81.6%
*-lft-identity81.6%
Simplified81.5%
Final simplification82.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(*
2.0
(*
R
(atan2
(sqrt
(+
t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(sqrt
(-
1.0
(+
(*
(cos phi1)
(*
(cos phi2)
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0)))
t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
return 2.0 * (R * atan2(sqrt((t_0 + (cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))), sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0))) + t_0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = ((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
code = 2.0d0 * (r * atan2(sqrt((t_0 + (cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))))), sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (((sin((lambda1 / 2.0d0)) * cos((lambda2 / 2.0d0))) - (cos((lambda1 / 2.0d0)) * sin((lambda2 / 2.0d0)))) ** 2.0d0))) + t_0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
return 2.0 * (R * Math.atan2(Math.sqrt((t_0 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))))), Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(((Math.sin((lambda1 / 2.0)) * Math.cos((lambda2 / 2.0))) - (Math.cos((lambda1 / 2.0)) * Math.sin((lambda2 / 2.0)))), 2.0))) + t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) return 2.0 * (R * math.atan2(math.sqrt((t_0 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))), math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(((math.sin((lambda1 / 2.0)) * math.cos((lambda2 / 2.0))) - (math.cos((lambda1 / 2.0)) * math.sin((lambda2 / 2.0)))), 2.0))) + t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 return Float64(2.0 * Float64(R * atan(sqrt(Float64(t_0 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0))) + t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; tmp = 2.0 * (R * atan2(sqrt((t_0 + (cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))), sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))) ^ 2.0))) + t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(2.0 * N[(R * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right)}^{2}\right) + t\_0\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
div-sub62.4%
sin-diff63.7%
Applied egg-rr63.7%
div-sub62.4%
sin-diff63.7%
Applied egg-rr82.6%
Taylor expanded in R around 0 82.5%
*-commutative82.5%
metadata-eval82.5%
div-inv82.5%
div-sub82.5%
sin-diff83.1%
Applied egg-rr83.0%
Final simplification83.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (* (cos phi2) t_1))
(t_3 (sqrt (+ t_0 (* (cos phi1) t_2)))))
(if (or (<= phi1 -260.0) (not (<= phi1 4.5e+19)))
(* 2.0 (* R (atan2 t_3 (sqrt (- 1.0 (+ t_0 (* (cos phi1) t_1)))))))
(* 2.0 (* R (atan2 t_3 (sqrt (- 1.0 (+ t_0 t_2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = cos(phi2) * t_1;
double t_3 = sqrt((t_0 + (cos(phi1) * t_2)));
double tmp;
if ((phi1 <= -260.0) || !(phi1 <= 4.5e+19)) {
tmp = 2.0 * (R * atan2(t_3, sqrt((1.0 - (t_0 + (cos(phi1) * t_1))))));
} else {
tmp = 2.0 * (R * atan2(t_3, sqrt((1.0 - (t_0 + t_2)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: tmp
t_0 = ((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
t_1 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_2 = cos(phi2) * t_1
t_3 = sqrt((t_0 + (cos(phi1) * t_2)))
if ((phi1 <= (-260.0d0)) .or. (.not. (phi1 <= 4.5d+19))) then
tmp = 2.0d0 * (r * atan2(t_3, sqrt((1.0d0 - (t_0 + (cos(phi1) * t_1))))))
else
tmp = 2.0d0 * (r * atan2(t_3, sqrt((1.0d0 - (t_0 + t_2)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
double t_1 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = Math.cos(phi2) * t_1;
double t_3 = Math.sqrt((t_0 + (Math.cos(phi1) * t_2)));
double tmp;
if ((phi1 <= -260.0) || !(phi1 <= 4.5e+19)) {
tmp = 2.0 * (R * Math.atan2(t_3, Math.sqrt((1.0 - (t_0 + (Math.cos(phi1) * t_1))))));
} else {
tmp = 2.0 * (R * Math.atan2(t_3, Math.sqrt((1.0 - (t_0 + t_2)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) t_1 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_2 = math.cos(phi2) * t_1 t_3 = math.sqrt((t_0 + (math.cos(phi1) * t_2))) tmp = 0 if (phi1 <= -260.0) or not (phi1 <= 4.5e+19): tmp = 2.0 * (R * math.atan2(t_3, math.sqrt((1.0 - (t_0 + (math.cos(phi1) * t_1)))))) else: tmp = 2.0 * (R * math.atan2(t_3, math.sqrt((1.0 - (t_0 + t_2))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(cos(phi2) * t_1) t_3 = sqrt(Float64(t_0 + Float64(cos(phi1) * t_2))) tmp = 0.0 if ((phi1 <= -260.0) || !(phi1 <= 4.5e+19)) tmp = Float64(2.0 * Float64(R * atan(t_3, sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * t_1))))))); else tmp = Float64(2.0 * Float64(R * atan(t_3, sqrt(Float64(1.0 - Float64(t_0 + t_2)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; t_1 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_2 = cos(phi2) * t_1; t_3 = sqrt((t_0 + (cos(phi1) * t_2))); tmp = 0.0; if ((phi1 <= -260.0) || ~((phi1 <= 4.5e+19))) tmp = 2.0 * (R * atan2(t_3, sqrt((1.0 - (t_0 + (cos(phi1) * t_1)))))); else tmp = 2.0 * (R * atan2(t_3, sqrt((1.0 - (t_0 + t_2))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -260.0], N[Not[LessEqual[phi1, 4.5e+19]], $MachinePrecision]], N[(2.0 * N[(R * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(2.0 * N[(R * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(t$95$0 + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \cos \phi_2 \cdot t\_1\\
t_3 := \sqrt{t\_0 + \cos \phi_1 \cdot t\_2}\\
\mathbf{if}\;\phi_1 \leq -260 \lor \neg \left(\phi_1 \leq 4.5 \cdot 10^{+19}\right):\\
\;\;\;\;2 \cdot \left(R \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;2 \cdot \left(R \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \left(t\_0 + t\_2\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -260 or 4.5e19 < phi1 Initial program 46.9%
div-sub46.9%
sin-diff49.5%
Applied egg-rr49.5%
div-sub46.9%
sin-diff49.5%
Applied egg-rr85.5%
Taylor expanded in R around 0 85.5%
Taylor expanded in phi2 around 0 63.3%
*-commutative63.0%
Simplified63.3%
if -260 < phi1 < 4.5e19Initial program 76.3%
div-sub76.3%
sin-diff76.4%
Applied egg-rr76.4%
div-sub76.3%
sin-diff76.4%
Applied egg-rr79.9%
Taylor expanded in R around 0 79.9%
Taylor expanded in phi1 around 0 78.1%
Final simplification71.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(t_1 (cos (* phi1 0.5)))
(t_2 (sin (* phi1 0.5)))
(t_3
(pow (- (* (cos (* phi2 0.5)) t_2) (* t_1 (sin (* phi2 0.5)))) 2.0))
(t_4 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -0.0112) (not (<= phi2 2.2e-5)))
(*
2.0
(*
R
(atan2 (sqrt (+ t_3 (* (cos phi1) t_0))) (sqrt (- 1.0 (+ t_3 t_0))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_4 t_4))))
(sqrt
(-
(+ 1.0 (* phi2 (* t_2 t_1)))
(+
(*
(cos phi1)
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0))
(pow t_2 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = cos((phi1 * 0.5));
double t_2 = sin((phi1 * 0.5));
double t_3 = pow(((cos((phi2 * 0.5)) * t_2) - (t_1 * sin((phi2 * 0.5)))), 2.0);
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -0.0112) || !(phi2 <= 2.2e-5)) {
tmp = 2.0 * (R * atan2(sqrt((t_3 + (cos(phi1) * t_0))), sqrt((1.0 - (t_3 + t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_4 * t_4)))), sqrt(((1.0 + (phi2 * (t_2 * t_1))) - ((cos(phi1) * pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0)) + pow(t_2, 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)
t_1 = cos((phi1 * 0.5d0))
t_2 = sin((phi1 * 0.5d0))
t_3 = ((cos((phi2 * 0.5d0)) * t_2) - (t_1 * sin((phi2 * 0.5d0)))) ** 2.0d0
t_4 = sin(((lambda1 - lambda2) / 2.0d0))
if ((phi2 <= (-0.0112d0)) .or. (.not. (phi2 <= 2.2d-5))) then
tmp = 2.0d0 * (r * atan2(sqrt((t_3 + (cos(phi1) * t_0))), sqrt((1.0d0 - (t_3 + t_0)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_4 * t_4)))), sqrt(((1.0d0 + (phi2 * (t_2 * t_1))) - ((cos(phi1) * (((sin((lambda1 / 2.0d0)) * cos((lambda2 / 2.0d0))) - (cos((lambda1 / 2.0d0)) * sin((lambda2 / 2.0d0)))) ** 2.0d0)) + (t_2 ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = Math.cos((phi1 * 0.5));
double t_2 = Math.sin((phi1 * 0.5));
double t_3 = Math.pow(((Math.cos((phi2 * 0.5)) * t_2) - (t_1 * Math.sin((phi2 * 0.5)))), 2.0);
double t_4 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -0.0112) || !(phi2 <= 2.2e-5)) {
tmp = 2.0 * (R * Math.atan2(Math.sqrt((t_3 + (Math.cos(phi1) * t_0))), Math.sqrt((1.0 - (t_3 + t_0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_4 * t_4)))), Math.sqrt(((1.0 + (phi2 * (t_2 * t_1))) - ((Math.cos(phi1) * Math.pow(((Math.sin((lambda1 / 2.0)) * Math.cos((lambda2 / 2.0))) - (Math.cos((lambda1 / 2.0)) * Math.sin((lambda2 / 2.0)))), 2.0)) + Math.pow(t_2, 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_1 = math.cos((phi1 * 0.5)) t_2 = math.sin((phi1 * 0.5)) t_3 = math.pow(((math.cos((phi2 * 0.5)) * t_2) - (t_1 * math.sin((phi2 * 0.5)))), 2.0) t_4 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (phi2 <= -0.0112) or not (phi2 <= 2.2e-5): tmp = 2.0 * (R * math.atan2(math.sqrt((t_3 + (math.cos(phi1) * t_0))), math.sqrt((1.0 - (t_3 + t_0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_4 * t_4)))), math.sqrt(((1.0 + (phi2 * (t_2 * t_1))) - ((math.cos(phi1) * math.pow(((math.sin((lambda1 / 2.0)) * math.cos((lambda2 / 2.0))) - (math.cos((lambda1 / 2.0)) * math.sin((lambda2 / 2.0)))), 2.0)) + math.pow(t_2, 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(phi1 * 0.5)) t_3 = Float64(Float64(cos(Float64(phi2 * 0.5)) * t_2) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -0.0112) || !(phi2 <= 2.2e-5)) tmp = Float64(2.0 * Float64(R * atan(sqrt(Float64(t_3 + Float64(cos(phi1) * t_0))), sqrt(Float64(1.0 - Float64(t_3 + t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_4 * t_4)))), sqrt(Float64(Float64(1.0 + Float64(phi2 * Float64(t_2 * t_1))) - Float64(Float64(cos(phi1) * (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0)) + (t_2 ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0); t_1 = cos((phi1 * 0.5)); t_2 = sin((phi1 * 0.5)); t_3 = ((cos((phi2 * 0.5)) * t_2) - (t_1 * sin((phi2 * 0.5)))) ^ 2.0; t_4 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((phi2 <= -0.0112) || ~((phi2 <= 2.2e-5))) tmp = 2.0 * (R * atan2(sqrt((t_3 + (cos(phi1) * t_0))), sqrt((1.0 - (t_3 + t_0))))); else tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_4 * t_4)))), sqrt(((1.0 + (phi2 * (t_2 * t_1))) - ((cos(phi1) * (((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))) ^ 2.0)) + (t_2 ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.0112], N[Not[LessEqual[phi2, 2.2e-5]], $MachinePrecision]], N[(2.0 * N[(R * N[ArcTan[N[Sqrt[N[(t$95$3 + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 + t$95$0), $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[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(phi2 * N[(t$95$2 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_3 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_2 - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -0.0112 \lor \neg \left(\phi_2 \leq 2.2 \cdot 10^{-5}\right):\\
\;\;\;\;2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + \cos \phi_1 \cdot t\_0}}{\sqrt{1 - \left(t\_3 + t\_0\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_4 \cdot t\_4\right)}}{\sqrt{\left(1 + \phi_2 \cdot \left(t\_2 \cdot t\_1\right)\right) - \left(\cos \phi_1 \cdot {\left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right)}^{2} + {t\_2}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -0.0111999999999999999 or 2.1999999999999999e-5 < phi2 Initial program 45.3%
div-sub45.3%
sin-diff47.5%
Applied egg-rr47.5%
div-sub45.3%
sin-diff47.5%
Applied egg-rr81.8%
Taylor expanded in R around 0 81.8%
Taylor expanded in phi1 around 0 60.5%
if -0.0111999999999999999 < phi2 < 2.1999999999999999e-5Initial program 83.1%
associate-*l*83.1%
Simplified83.1%
Taylor expanded in phi2 around 0 83.1%
*-commutative83.5%
metadata-eval83.5%
div-inv83.5%
div-sub83.5%
sin-diff84.0%
Applied egg-rr83.6%
Final simplification71.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2
(pow (- (* (cos (* phi2 0.5)) t_0) (* t_1 (sin (* phi2 0.5)))) 2.0))
(t_3 (* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(t_4 (+ t_2 (* (cos phi1) t_3)))
(t_5 (+ t_2 t_3))
(t_6 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= phi2 -0.0112)
(* 2.0 (* R (atan2 (sqrt t_4) (sqrt (- 1.0 t_5)))))
(if (<= phi2 2e-6)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_6 t_6))))
(sqrt
(-
(+ 1.0 (* phi2 (* t_0 t_1)))
(+
(*
(cos phi1)
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0))
(pow t_0 2.0)))))))
(* 2.0 (* R (atan2 (sqrt t_5) (sqrt (- 1.0 t_4)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = pow(((cos((phi2 * 0.5)) * t_0) - (t_1 * sin((phi2 * 0.5)))), 2.0);
double t_3 = cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_4 = t_2 + (cos(phi1) * t_3);
double t_5 = t_2 + t_3;
double t_6 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi2 <= -0.0112) {
tmp = 2.0 * (R * atan2(sqrt(t_4), sqrt((1.0 - t_5))));
} else if (phi2 <= 2e-6) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_6 * t_6)))), sqrt(((1.0 + (phi2 * (t_0 * t_1))) - ((cos(phi1) * pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0)) + pow(t_0, 2.0))))));
} else {
tmp = 2.0 * (R * atan2(sqrt(t_5), sqrt((1.0 - 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) :: t_5
real(8) :: t_6
real(8) :: tmp
t_0 = sin((phi1 * 0.5d0))
t_1 = cos((phi1 * 0.5d0))
t_2 = ((cos((phi2 * 0.5d0)) * t_0) - (t_1 * sin((phi2 * 0.5d0)))) ** 2.0d0
t_3 = cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)
t_4 = t_2 + (cos(phi1) * t_3)
t_5 = t_2 + t_3
t_6 = sin(((lambda1 - lambda2) / 2.0d0))
if (phi2 <= (-0.0112d0)) then
tmp = 2.0d0 * (r * atan2(sqrt(t_4), sqrt((1.0d0 - t_5))))
else if (phi2 <= 2d-6) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_6 * t_6)))), sqrt(((1.0d0 + (phi2 * (t_0 * t_1))) - ((cos(phi1) * (((sin((lambda1 / 2.0d0)) * cos((lambda2 / 2.0d0))) - (cos((lambda1 / 2.0d0)) * sin((lambda2 / 2.0d0)))) ** 2.0d0)) + (t_0 ** 2.0d0))))))
else
tmp = 2.0d0 * (r * atan2(sqrt(t_5), sqrt((1.0d0 - 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.cos((phi1 * 0.5));
double t_2 = Math.pow(((Math.cos((phi2 * 0.5)) * t_0) - (t_1 * Math.sin((phi2 * 0.5)))), 2.0);
double t_3 = Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_4 = t_2 + (Math.cos(phi1) * t_3);
double t_5 = t_2 + t_3;
double t_6 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi2 <= -0.0112) {
tmp = 2.0 * (R * Math.atan2(Math.sqrt(t_4), Math.sqrt((1.0 - t_5))));
} else if (phi2 <= 2e-6) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_6 * t_6)))), Math.sqrt(((1.0 + (phi2 * (t_0 * t_1))) - ((Math.cos(phi1) * Math.pow(((Math.sin((lambda1 / 2.0)) * Math.cos((lambda2 / 2.0))) - (Math.cos((lambda1 / 2.0)) * Math.sin((lambda2 / 2.0)))), 2.0)) + Math.pow(t_0, 2.0))))));
} else {
tmp = 2.0 * (R * Math.atan2(Math.sqrt(t_5), Math.sqrt((1.0 - t_4))));
}
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.pow(((math.cos((phi2 * 0.5)) * t_0) - (t_1 * math.sin((phi2 * 0.5)))), 2.0) t_3 = math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_4 = t_2 + (math.cos(phi1) * t_3) t_5 = t_2 + t_3 t_6 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if phi2 <= -0.0112: tmp = 2.0 * (R * math.atan2(math.sqrt(t_4), math.sqrt((1.0 - t_5)))) elif phi2 <= 2e-6: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_6 * t_6)))), math.sqrt(((1.0 + (phi2 * (t_0 * t_1))) - ((math.cos(phi1) * math.pow(((math.sin((lambda1 / 2.0)) * math.cos((lambda2 / 2.0))) - (math.cos((lambda1 / 2.0)) * math.sin((lambda2 / 2.0)))), 2.0)) + math.pow(t_0, 2.0)))))) else: tmp = 2.0 * (R * math.atan2(math.sqrt(t_5), math.sqrt((1.0 - t_4)))) 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 = Float64(Float64(cos(Float64(phi2 * 0.5)) * t_0) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_3 = Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) t_4 = Float64(t_2 + Float64(cos(phi1) * t_3)) t_5 = Float64(t_2 + t_3) t_6 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (phi2 <= -0.0112) tmp = Float64(2.0 * Float64(R * atan(sqrt(t_4), sqrt(Float64(1.0 - t_5))))); elseif (phi2 <= 2e-6) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_6 * t_6)))), sqrt(Float64(Float64(1.0 + Float64(phi2 * Float64(t_0 * t_1))) - Float64(Float64(cos(phi1) * (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0)) + (t_0 ^ 2.0))))))); else tmp = Float64(2.0 * Float64(R * atan(sqrt(t_5), sqrt(Float64(1.0 - t_4))))); 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 = ((cos((phi2 * 0.5)) * t_0) - (t_1 * sin((phi2 * 0.5)))) ^ 2.0; t_3 = cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0); t_4 = t_2 + (cos(phi1) * t_3); t_5 = t_2 + t_3; t_6 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if (phi2 <= -0.0112) tmp = 2.0 * (R * atan2(sqrt(t_4), sqrt((1.0 - t_5)))); elseif (phi2 <= 2e-6) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_6 * t_6)))), sqrt(((1.0 + (phi2 * (t_0 * t_1))) - ((cos(phi1) * (((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))) ^ 2.0)) + (t_0 ^ 2.0)))))); else tmp = 2.0 * (R * atan2(sqrt(t_5), sqrt((1.0 - 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[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(t$95$2 + N[(N[Cos[phi1], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(t$95$2 + t$95$3), $MachinePrecision]}, Block[{t$95$6 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -0.0112], N[(2.0 * N[(R * N[ArcTan[N[Sqrt[t$95$4], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$5), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2e-6], 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$6 * t$95$6), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(phi2 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(2.0 * N[(R * N[ArcTan[N[Sqrt[t$95$5], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$4), $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 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_0 - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_3 := \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_4 := t\_2 + \cos \phi_1 \cdot t\_3\\
t_5 := t\_2 + t\_3\\
t_6 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -0.0112:\\
\;\;\;\;2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{t\_4}}{\sqrt{1 - t\_5}}\right)\\
\mathbf{elif}\;\phi_2 \leq 2 \cdot 10^{-6}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_6 \cdot t\_6\right)}}{\sqrt{\left(1 + \phi_2 \cdot \left(t\_0 \cdot t\_1\right)\right) - \left(\cos \phi_1 \cdot {\left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right)}^{2} + {t\_0}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{t\_5}}{\sqrt{1 - t\_4}}\right)\\
\end{array}
\end{array}
if phi2 < -0.0111999999999999999Initial program 49.8%
div-sub49.8%
sin-diff51.8%
Applied egg-rr51.8%
div-sub49.8%
sin-diff51.8%
Applied egg-rr85.2%
Taylor expanded in R around 0 85.2%
Taylor expanded in phi1 around 0 63.3%
if -0.0111999999999999999 < phi2 < 1.99999999999999991e-6Initial program 83.1%
associate-*l*83.1%
Simplified83.1%
Taylor expanded in phi2 around 0 83.1%
*-commutative83.5%
metadata-eval83.5%
div-inv83.5%
div-sub83.5%
sin-diff84.0%
Applied egg-rr83.6%
if 1.99999999999999991e-6 < phi2 Initial program 41.7%
div-sub41.7%
sin-diff44.1%
Applied egg-rr44.1%
div-sub41.7%
sin-diff44.1%
Applied egg-rr79.1%
Taylor expanded in R around 0 79.0%
Taylor expanded in phi1 around 0 59.5%
Final simplification71.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(*
2.0
(*
R
(atan2
(sqrt
(+
t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(sqrt
(+
1.0
(-
(*
(cos phi1)
(* (cos phi2) (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))
t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
return 2.0 * (R * atan2(sqrt((t_0 + (cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))) - t_0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = ((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
code = 2.0d0 * (r * atan2(sqrt((t_0 + (cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))))), sqrt((1.0d0 + ((cos(phi1) * (cos(phi2) * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0))) - t_0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
return 2.0 * (R * Math.atan2(Math.sqrt((t_0 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))))), Math.sqrt((1.0 + ((Math.cos(phi1) * (Math.cos(phi2) * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))) - t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) return 2.0 * (R * math.atan2(math.sqrt((t_0 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))), math.sqrt((1.0 + ((math.cos(phi1) * (math.cos(phi2) * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5))) - t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 return Float64(2.0 * Float64(R * atan(sqrt(Float64(t_0 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))), sqrt(Float64(1.0 + Float64(Float64(cos(phi1) * Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))) - t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; tmp = 2.0 * (R * atan2(sqrt((t_0 + (cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))) - t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(2.0 * N[(R * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}}{\sqrt{1 + \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)\right) - t\_0\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
div-sub62.4%
sin-diff63.7%
Applied egg-rr63.7%
div-sub62.4%
sin-diff63.7%
Applied egg-rr82.6%
Taylor expanded in R around 0 82.5%
*-commutative82.5%
metadata-eval82.5%
div-inv82.5%
pow282.5%
sin-mult82.6%
Applied egg-rr82.6%
div-sub82.6%
+-inverses82.6%
cos-082.6%
metadata-eval82.6%
associate-*r*82.6%
metadata-eval82.6%
*-lft-identity82.6%
Simplified82.6%
Final simplification82.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_1
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)))
(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 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0))), 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 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0))), 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 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0))), 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 * ((math.cos(phi1) * math.cos(phi2)) * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0))), 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(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0))), 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 * ((cos(phi1) * cos(phi2)) * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0))), 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[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $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(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
div-sub62.4%
sin-diff63.7%
Applied egg-rr63.7%
Final simplification63.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_1
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)))
(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 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0))), 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 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0))), 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 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0))), 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 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0))), 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(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0))), sqrt(Float64(Float64(1.0 - (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 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0))), 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[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}}}{\sqrt{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
div-sub62.4%
sin-diff63.7%
Applied egg-rr63.7%
Final simplification63.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
t_0))
(sqrt (- 1.0 (+ t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * atan2(sqrt((pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + t_0)), sqrt((1.0 - (t_0 + pow(sin((0.5 * (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
t_0 = cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0) + t_0)), sqrt((1.0d0 - (t_0 + (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0) + t_0)), Math.sqrt((1.0 - (t_0 + Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) + t_0)), math.sqrt((1.0 - (t_0 + math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + t_0)), sqrt(Float64(1.0 - Float64(t_0 + (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)); tmp = R * (2.0 * atan2(sqrt(((((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0) + t_0)), sqrt((1.0 - (t_0 + (sin((0.5 * (phi1 - phi2))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \left(\cos \phi_2 \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(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + t\_0}}{\sqrt{1 - \left(t\_0 + {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
div-sub62.4%
sin-diff63.7%
Applied egg-rr63.7%
Taylor expanded in phi1 around 0 63.7%
Final simplification63.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_1))))
(sqrt
(fabs
(+
(fma
t_0
(+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))
-1.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_1)))), sqrt(fabs((fma(t_0, (0.5 + (cos((lambda1 - lambda2)) * -0.5)), pow(sin((0.5 * (phi1 - phi2))), 2.0)) + -1.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_1)))), sqrt(abs(Float64(fma(t_0, Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) + -1.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, 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$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(N[(t$95$0 * N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left|\mathsf{fma}\left(t\_0, 0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) + -1\right|}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
Applied egg-rr62.6%
unpow1/262.6%
unpow262.6%
rem-sqrt-square62.6%
fma-define62.6%
*-commutative62.6%
fma-define62.6%
Simplified62.6%
Final simplification62.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(if (or (<= t_1 -0.1) (not (<= t_1 0.1)))
(*
(atan2
(hypot
(sin (* phi1 0.5))
(* (sin (* 0.5 (- lambda1 lambda2))) (sqrt (cos phi1))))
(sqrt (- 1.0 (fma (+ 0.5 (* (cos (- lambda1 lambda2)) -0.5)) t_0 t_2))))
(* 2.0 R))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_1 (* t_0 t_1))
(pow (sin (/ (* phi1 (- 1.0 (/ phi2 phi1))) 2.0)) 2.0)))
(sqrt (- 1.0 t_2))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
double tmp;
if ((t_1 <= -0.1) || !(t_1 <= 0.1)) {
tmp = atan2(hypot(sin((phi1 * 0.5)), (sin((0.5 * (lambda1 - lambda2))) * sqrt(cos(phi1)))), sqrt((1.0 - fma((0.5 + (cos((lambda1 - lambda2)) * -0.5)), t_0, t_2)))) * (2.0 * R);
} else {
tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_1)) + pow(sin(((phi1 * (1.0 - (phi2 / phi1))) / 2.0)), 2.0))), sqrt((1.0 - t_2))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0 tmp = 0.0 if ((t_1 <= -0.1) || !(t_1 <= 0.1)) tmp = Float64(atan(hypot(sin(Float64(phi1 * 0.5)), Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(cos(phi1)))), sqrt(Float64(1.0 - fma(Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), t_0, t_2)))) * Float64(2.0 * R)); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_1)) + (sin(Float64(Float64(phi1 * Float64(1.0 - Float64(phi2 / phi1))) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - t_2))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[t$95$1, -0.1], N[Not[LessEqual[t$95$1, 0.1]], $MachinePrecision]], N[(N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] * t$95$0 + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 * N[(1.0 - N[(phi2 / phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\\
\mathbf{if}\;t\_1 \leq -0.1 \lor \neg \left(t\_1 \leq 0.1\right):\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_1}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, t\_0, t\_2\right)}} \cdot \left(2 \cdot R\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 \cdot \left(1 - \frac{\phi_2}{\phi_1}\right)}{2}\right)}^{2}}}{\sqrt{1 - t\_2}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.10000000000000001 or 0.10000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 58.8%
Simplified58.7%
Applied egg-rr40.2%
unpow140.2%
Simplified40.2%
Taylor expanded in phi2 around 0 32.5%
Taylor expanded in phi2 around 0 36.1%
if -0.10000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.10000000000000001Initial program 69.5%
Taylor expanded in phi1 around inf 59.5%
mul-1-neg59.5%
unsub-neg59.5%
Simplified59.5%
Taylor expanded in lambda1 around 0 58.0%
Taylor expanded in lambda2 around 0 55.9%
Final simplification42.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -2.2e-9) (not (<= phi2 1.7e-5)))
(*
(atan2
(sqrt (+ (* (cos phi2) t_0) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
1.0
(fma
(+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))
t_2
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))
(* 2.0 R))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_1 (* t_2 t_1))
(pow (sin (/ (* phi1 (- 1.0 (/ phi2 phi1))) 2.0)) 2.0)))
(sqrt
(- 1.0 (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -2.2e-9) || !(phi2 <= 1.7e-5)) {
tmp = atan2(sqrt(((cos(phi2) * t_0) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - fma((0.5 + (cos((lambda1 - lambda2)) * -0.5)), t_2, pow(sin((0.5 * (phi1 - phi2))), 2.0))))) * (2.0 * R);
} else {
tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_2 * t_1)) + pow(sin(((phi1 * (1.0 - (phi2 / phi1))) / 2.0)), 2.0))), sqrt((1.0 - ((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -2.2e-9) || !(phi2 <= 1.7e-5)) tmp = Float64(atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), t_2, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))) * Float64(2.0 * R)); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_2 * t_1)) + (sin(Float64(Float64(phi1 * Float64(1.0 - Float64(phi2 / phi1))) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -2.2e-9], N[Not[LessEqual[phi2, 1.7e-5]], $MachinePrecision]], N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] * t$95$2 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$2 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 * N[(1.0 - N[(phi2 / phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -2.2 \cdot 10^{-9} \lor \neg \left(\phi_2 \leq 1.7 \cdot 10^{-5}\right):\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, t\_2, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_2 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 \cdot \left(1 - \frac{\phi_2}{\phi_1}\right)}{2}\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -2.1999999999999998e-9 or 1.7e-5 < phi2 Initial program 44.9%
Simplified44.9%
Applied egg-rr24.3%
unpow124.3%
Simplified24.3%
Taylor expanded in phi1 around 0 46.5%
if -2.1999999999999998e-9 < phi2 < 1.7e-5Initial program 84.2%
Taylor expanded in phi1 around inf 84.2%
mul-1-neg84.2%
unsub-neg84.2%
Simplified84.2%
Taylor expanded in phi2 around 0 84.2%
Final simplification63.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -2.2e-9) (not (<= phi2 0.000115)))
(*
(atan2
(sqrt (+ (* (cos phi2) t_0) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
1.0
(fma
(+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))
t_1
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))
(* 2.0 R))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_1 (* t_2 t_2))))
(sqrt
(- 1.0 (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -2.2e-9) || !(phi2 <= 0.000115)) {
tmp = atan2(sqrt(((cos(phi2) * t_0) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - fma((0.5 + (cos((lambda1 - lambda2)) * -0.5)), t_1, pow(sin((0.5 * (phi1 - phi2))), 2.0))))) * (2.0 * R);
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_2 * t_2)))), sqrt((1.0 - ((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -2.2e-9) || !(phi2 <= 0.000115)) tmp = Float64(atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), t_1, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))) * Float64(2.0 * R)); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(t_2 * t_2)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -2.2e-9], N[Not[LessEqual[phi2, 0.000115]], $MachinePrecision]], N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] * t$95$1 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $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$1 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -2.2 \cdot 10^{-9} \lor \neg \left(\phi_2 \leq 0.000115\right):\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, t\_1, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \left(t\_2 \cdot t\_2\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -2.1999999999999998e-9 or 1.15e-4 < phi2 Initial program 44.9%
Simplified44.9%
Applied egg-rr24.3%
unpow124.3%
Simplified24.3%
Taylor expanded in phi1 around 0 46.5%
if -2.1999999999999998e-9 < phi2 < 1.15e-4Initial program 84.2%
associate-*l*84.2%
Simplified84.2%
Taylor expanded in phi2 around 0 84.2%
Final simplification63.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt (+ 1.0 (- (/ (+ (cos (- phi1 phi2)) -1.0) 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 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt((1.0 + (((cos((phi1 - phi2)) + -1.0) / 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 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt((1.0d0 + (((cos((phi1 - phi2)) + (-1.0d0)) / 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 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt((1.0 + (((Math.cos((phi1 - phi2)) + -1.0) / 2.0) - t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt((1.0 + (((math.cos((phi1 - phi2)) + -1.0) / 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(Float64(cos(phi1) * cos(phi2)) * t_0)) 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(Float64(Float64(cos(Float64(phi1 - phi2)) + -1.0) / 2.0) - t_1)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt((1.0 + (((cos((phi1 - phi2)) + -1.0) / 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[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $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[(N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + -1.0), $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(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\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(\frac{\cos \left(\phi_1 - \phi_2\right) + -1}{2} - t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
unpow262.4%
sin-mult62.5%
div-inv62.5%
metadata-eval62.5%
div-inv62.5%
metadata-eval62.5%
div-inv62.5%
metadata-eval62.5%
div-inv62.5%
metadata-eval62.5%
Applied egg-rr62.5%
+-inverses62.5%
cos-062.5%
distribute-lft-out62.5%
metadata-eval62.5%
*-rgt-identity62.5%
Simplified62.5%
Final simplification62.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_1))))
(sqrt
(-
(- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(* t_0 (- 0.5 (* 0.5 (cos (- lambda1 lambda2))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)) - (t_0 * (0.5 - (0.5 * cos((lambda1 - lambda2)))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_1 * t_1)))), sqrt(((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)) - (t_0 * (0.5d0 - (0.5d0 * cos((lambda1 - lambda2)))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_1)))), Math.sqrt(((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)) - (t_0 * (0.5 - (0.5 * Math.cos((lambda1 - lambda2)))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_1)))), math.sqrt(((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)) - (t_0 * (0.5 - (0.5 * math.cos((lambda1 - lambda2)))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_1)))), sqrt(Float64(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) - Float64(t_0 * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0)) - (t_0 * (0.5 - (0.5 * cos((lambda1 - lambda2))))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, 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$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(t$95$0 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left(1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) - t\_0 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
cancel-sign-sub-inv62.4%
div-inv62.4%
metadata-eval62.4%
sqr-sin-a62.4%
cos-262.4%
cos-sum62.4%
add-log-exp21.7%
add-log-exp21.7%
sum-log21.7%
exp-sqrt21.7%
exp-sqrt21.7%
Applied egg-rr62.4%
Final simplification62.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1
(sqrt
(-
1.0
(fma
(+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))
(* (cos phi1) (cos phi2))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(if (or (<= phi2 -3.7e-23) (not (<= phi2 8.2e-17)))
(*
(atan2 (sqrt (+ (* (cos phi2) t_0) (pow (sin (* phi2 -0.5)) 2.0))) t_1)
(* 2.0 R))
(*
(atan2 (sqrt (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0))) t_1)
(* 2.0 R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sqrt((1.0 - fma((0.5 + (cos((lambda1 - lambda2)) * -0.5)), (cos(phi1) * cos(phi2)), pow(sin((0.5 * (phi1 - phi2))), 2.0))));
double tmp;
if ((phi2 <= -3.7e-23) || !(phi2 <= 8.2e-17)) {
tmp = atan2(sqrt(((cos(phi2) * t_0) + pow(sin((phi2 * -0.5)), 2.0))), t_1) * (2.0 * R);
} else {
tmp = atan2(sqrt(((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))), t_1) * (2.0 * R);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sqrt(Float64(1.0 - fma(Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), Float64(cos(phi1) * cos(phi2)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))) tmp = 0.0 if ((phi2 <= -3.7e-23) || !(phi2 <= 8.2e-17)) tmp = Float64(atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), t_1) * Float64(2.0 * R)); else tmp = Float64(atan(sqrt(Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), t_1) * Float64(2.0 * R)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - N[(N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -3.7e-23], N[Not[LessEqual[phi2, 8.2e-17]], $MachinePrecision]], N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sqrt{1 - \mathsf{fma}\left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, \cos \phi_1 \cdot \cos \phi_2, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}\\
\mathbf{if}\;\phi_2 \leq -3.7 \cdot 10^{-23} \lor \neg \left(\phi_2 \leq 8.2 \cdot 10^{-17}\right):\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{t\_1} \cdot \left(2 \cdot R\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{t\_1} \cdot \left(2 \cdot R\right)\\
\end{array}
\end{array}
if phi2 < -3.7000000000000003e-23 or 8.2000000000000001e-17 < phi2 Initial program 45.8%
Simplified45.8%
Applied egg-rr25.7%
unpow125.7%
Simplified25.7%
Taylor expanded in phi1 around 0 47.0%
if -3.7000000000000003e-23 < phi2 < 8.2000000000000001e-17Initial program 85.3%
Simplified85.2%
Applied egg-rr67.1%
unpow167.1%
Simplified67.1%
Taylor expanded in phi2 around 0 64.0%
Taylor expanded in phi2 around 0 82.1%
Final simplification61.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(t_1 (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))))
(if (or (<= phi2 -3.7e-23) (not (<= phi2 0.115)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (* phi2 -0.5)) 2.0) t_1))
(sqrt (- 1.0 (+ t_0 (* (cos phi1) t_1)))))))
(*
(atan2
(sqrt
(+
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* phi1 0.5)) 2.0)))
(sqrt
(-
1.0
(fma
(+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))
(* (cos phi1) (cos phi2))
t_0))))
(* 2.0 R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
double t_1 = cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0);
double tmp;
if ((phi2 <= -3.7e-23) || !(phi2 <= 0.115)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + t_1)), sqrt((1.0 - (t_0 + (cos(phi1) * t_1))))));
} else {
tmp = atan2(sqrt(((cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + pow(sin((phi1 * 0.5)), 2.0))), sqrt((1.0 - fma((0.5 + (cos((lambda1 - lambda2)) * -0.5)), (cos(phi1) * cos(phi2)), t_0)))) * (2.0 * R);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0 t_1 = Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0)) tmp = 0.0 if ((phi2 <= -3.7e-23) || !(phi2 <= 0.115)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * t_1))))))); else tmp = Float64(atan(sqrt(Float64(Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), Float64(cos(phi1) * cos(phi2)), t_0)))) * Float64(2.0 * R)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -3.7e-23], N[Not[LessEqual[phi2, 0.115]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(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[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\\
t_1 := \cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -3.7 \cdot 10^{-23} \lor \neg \left(\phi_2 \leq 0.115\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + t\_1}}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, \cos \phi_1 \cdot \cos \phi_2, t\_0\right)}} \cdot \left(2 \cdot R\right)\\
\end{array}
\end{array}
if phi2 < -3.7000000000000003e-23 or 0.115000000000000005 < phi2 Initial program 44.6%
Taylor expanded in phi1 around inf 26.6%
mul-1-neg26.6%
unsub-neg26.6%
Simplified26.6%
Taylor expanded in lambda1 around 0 20.9%
Taylor expanded in lambda1 around 0 21.3%
Taylor expanded in phi1 around 0 35.2%
if -3.7000000000000003e-23 < phi2 < 0.115000000000000005Initial program 85.4%
Simplified85.3%
Applied egg-rr67.3%
unpow167.3%
Simplified67.3%
Taylor expanded in phi2 around 0 63.0%
Taylor expanded in phi2 around 0 80.9%
Final simplification55.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* lambda2 -0.5)) 2.0))
(t_1 (sin (* 0.5 (- phi1 phi2))))
(t_2 (* (cos phi1) (cos phi2))))
(if (or (<= phi1 -5.8e-59) (not (<= phi1 0.00085)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (* phi1 0.5)) 2.0) (* (cos phi1) t_0)))
(sqrt (- 1.0 (+ (pow t_1 2.0) (* (cos phi1) (* (cos phi2) t_0))))))))
(*
(atan2
(hypot t_1 (* (sin (* 0.5 (- lambda1 lambda2))) (sqrt t_2)))
(sqrt
(-
1.0
(fma
(+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))
t_2
(pow (sin (* phi2 -0.5)) 2.0)))))
(* 2.0 R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((lambda2 * -0.5)), 2.0);
double t_1 = sin((0.5 * (phi1 - phi2)));
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if ((phi1 <= -5.8e-59) || !(phi1 <= 0.00085)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * t_0))), sqrt((1.0 - (pow(t_1, 2.0) + (cos(phi1) * (cos(phi2) * t_0)))))));
} else {
tmp = atan2(hypot(t_1, (sin((0.5 * (lambda1 - lambda2))) * sqrt(t_2))), sqrt((1.0 - fma((0.5 + (cos((lambda1 - lambda2)) * -0.5)), t_2, pow(sin((phi2 * -0.5)), 2.0))))) * (2.0 * R);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(lambda2 * -0.5)) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi1 <= -5.8e-59) || !(phi1 <= 0.00085)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * t_0))), sqrt(Float64(1.0 - Float64((t_1 ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * t_0)))))))); else tmp = Float64(atan(hypot(t_1, Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(t_2))), sqrt(Float64(1.0 - fma(Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), t_2, (sin(Float64(phi2 * -0.5)) ^ 2.0))))) * Float64(2.0 * R)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi1, -5.8e-59], N[Not[LessEqual[phi1, 0.00085]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[t$95$1, 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[t$95$2], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] * t$95$2 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_1 \leq -5.8 \cdot 10^{-59} \lor \neg \left(\phi_1 \leq 0.00085\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot t\_0}}{\sqrt{1 - \left({t\_1}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot t\_0\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{t\_2}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, t\_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)\\
\end{array}
\end{array}
if phi1 < -5.80000000000000033e-59 or 8.49999999999999953e-4 < phi1 Initial program 48.2%
Taylor expanded in phi1 around inf 47.3%
mul-1-neg47.3%
unsub-neg47.3%
Simplified47.3%
Taylor expanded in lambda1 around 0 38.5%
Taylor expanded in lambda1 around 0 38.9%
Taylor expanded in phi2 around 0 39.3%
if -5.80000000000000033e-59 < phi1 < 8.49999999999999953e-4Initial program 77.9%
Simplified77.8%
Applied egg-rr60.9%
unpow160.9%
Simplified60.9%
Taylor expanded in phi1 around 0 60.9%
*-commutative60.9%
Simplified60.9%
Final simplification49.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))
(t_1 (sin (* 0.5 (- phi1 phi2))))
(t_2 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -3e-24) (not (<= phi2 1.2e-7)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (* phi2 -0.5)) 2.0) t_0))
(sqrt (- 1.0 (+ (pow t_1 2.0) (* (cos phi1) t_0)))))))
(*
(atan2
(hypot t_1 (* (sin (* 0.5 (- lambda1 lambda2))) (sqrt t_2)))
(sqrt
(-
1.0
(fma
(+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))
t_2
(pow (sin (* phi1 0.5)) 2.0)))))
(* 2.0 R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0);
double t_1 = sin((0.5 * (phi1 - phi2)));
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -3e-24) || !(phi2 <= 1.2e-7)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + t_0)), sqrt((1.0 - (pow(t_1, 2.0) + (cos(phi1) * t_0))))));
} else {
tmp = atan2(hypot(t_1, (sin((0.5 * (lambda1 - lambda2))) * sqrt(t_2))), sqrt((1.0 - fma((0.5 + (cos((lambda1 - lambda2)) * -0.5)), t_2, pow(sin((phi1 * 0.5)), 2.0))))) * (2.0 * R);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0)) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -3e-24) || !(phi2 <= 1.2e-7)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + t_0)), sqrt(Float64(1.0 - Float64((t_1 ^ 2.0) + Float64(cos(phi1) * t_0))))))); else tmp = Float64(atan(hypot(t_1, Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(t_2))), sqrt(Float64(1.0 - fma(Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), t_2, (sin(Float64(phi1 * 0.5)) ^ 2.0))))) * Float64(2.0 * R)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -3e-24], N[Not[LessEqual[phi2, 1.2e-7]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[t$95$1, 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[t$95$2], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] * t$95$2 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -3 \cdot 10^{-24} \lor \neg \left(\phi_2 \leq 1.2 \cdot 10^{-7}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + t\_0}}{\sqrt{1 - \left({t\_1}^{2} + \cos \phi_1 \cdot t\_0\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{t\_2}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, t\_2, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)\\
\end{array}
\end{array}
if phi2 < -2.99999999999999995e-24 or 1.19999999999999989e-7 < phi2 Initial program 45.4%
Taylor expanded in phi1 around inf 27.7%
mul-1-neg27.7%
unsub-neg27.7%
Simplified27.7%
Taylor expanded in lambda1 around 0 21.2%
Taylor expanded in lambda1 around 0 21.5%
Taylor expanded in phi1 around 0 34.8%
if -2.99999999999999995e-24 < phi2 < 1.19999999999999989e-7Initial program 85.4%
Simplified85.4%
Applied egg-rr68.3%
unpow168.3%
Simplified68.3%
Taylor expanded in phi2 around 0 68.3%
Final simplification49.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(t_1 (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))))
(if (or (<= phi2 -3e-24) (not (<= phi2 1.25e-20)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (* phi2 -0.5)) 2.0) t_1))
(sqrt (- 1.0 (+ t_0 (* (cos phi1) t_1)))))))
(*
(atan2
(hypot
(sin (* phi1 0.5))
(sqrt (* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt
(-
1.0
(fma
(+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))
(* (cos phi1) (cos phi2))
t_0))))
(* 2.0 R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
double t_1 = cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0);
double tmp;
if ((phi2 <= -3e-24) || !(phi2 <= 1.25e-20)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + t_1)), sqrt((1.0 - (t_0 + (cos(phi1) * t_1))))));
} else {
tmp = atan2(hypot(sin((phi1 * 0.5)), sqrt((cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt((1.0 - fma((0.5 + (cos((lambda1 - lambda2)) * -0.5)), (cos(phi1) * cos(phi2)), t_0)))) * (2.0 * R);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0 t_1 = Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0)) tmp = 0.0 if ((phi2 <= -3e-24) || !(phi2 <= 1.25e-20)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * t_1))))))); else tmp = Float64(atan(hypot(sin(Float64(phi1 * 0.5)), sqrt(Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64(1.0 - fma(Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), Float64(cos(phi1) * cos(phi2)), t_0)))) * Float64(2.0 * R)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -3e-24], N[Not[LessEqual[phi2, 1.25e-20]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\\
t_1 := \cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -3 \cdot 10^{-24} \lor \neg \left(\phi_2 \leq 1.25 \cdot 10^{-20}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + t\_1}}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), \sqrt{\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, \cos \phi_1 \cdot \cos \phi_2, t\_0\right)}} \cdot \left(2 \cdot R\right)\\
\end{array}
\end{array}
if phi2 < -2.99999999999999995e-24 or 1.25e-20 < phi2 Initial program 46.5%
Taylor expanded in phi1 around inf 29.2%
mul-1-neg29.2%
unsub-neg29.2%
Simplified29.2%
Taylor expanded in lambda1 around 0 21.7%
Taylor expanded in lambda1 around 0 22.0%
Taylor expanded in phi1 around 0 34.9%
if -2.99999999999999995e-24 < phi2 < 1.25e-20Initial program 85.0%
Simplified85.0%
Applied egg-rr68.3%
unpow168.3%
Simplified68.3%
Taylor expanded in phi2 around 0 65.2%
Taylor expanded in phi2 around 0 81.8%
+-commutative81.8%
*-commutative81.8%
unpow281.8%
rem-square-sqrt67.0%
hypot-undefine67.1%
*-commutative67.1%
*-commutative67.1%
Simplified67.1%
Final simplification48.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(t_1 (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))))
(if (or (<= phi2 -6e-25) (not (<= phi2 8.8e-21)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (* phi2 -0.5)) 2.0) t_1))
(sqrt (- 1.0 (+ t_0 (* (cos phi1) t_1)))))))
(*
(atan2
(hypot
(sin (* phi1 0.5))
(* (sin (* 0.5 (- lambda1 lambda2))) (sqrt (cos phi1))))
(sqrt
(-
1.0
(fma
(+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))
(* (cos phi1) (cos phi2))
t_0))))
(* 2.0 R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
double t_1 = cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0);
double tmp;
if ((phi2 <= -6e-25) || !(phi2 <= 8.8e-21)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + t_1)), sqrt((1.0 - (t_0 + (cos(phi1) * t_1))))));
} else {
tmp = atan2(hypot(sin((phi1 * 0.5)), (sin((0.5 * (lambda1 - lambda2))) * sqrt(cos(phi1)))), sqrt((1.0 - fma((0.5 + (cos((lambda1 - lambda2)) * -0.5)), (cos(phi1) * cos(phi2)), t_0)))) * (2.0 * R);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0 t_1 = Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0)) tmp = 0.0 if ((phi2 <= -6e-25) || !(phi2 <= 8.8e-21)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * t_1))))))); else tmp = Float64(atan(hypot(sin(Float64(phi1 * 0.5)), Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(cos(phi1)))), sqrt(Float64(1.0 - fma(Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), Float64(cos(phi1) * cos(phi2)), t_0)))) * Float64(2.0 * R)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -6e-25], N[Not[LessEqual[phi2, 8.8e-21]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\\
t_1 := \cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -6 \cdot 10^{-25} \lor \neg \left(\phi_2 \leq 8.8 \cdot 10^{-21}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + t\_1}}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_1}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, \cos \phi_1 \cdot \cos \phi_2, t\_0\right)}} \cdot \left(2 \cdot R\right)\\
\end{array}
\end{array}
if phi2 < -5.9999999999999995e-25 or 8.8000000000000002e-21 < phi2 Initial program 46.5%
Taylor expanded in phi1 around inf 29.2%
mul-1-neg29.2%
unsub-neg29.2%
Simplified29.2%
Taylor expanded in lambda1 around 0 21.7%
Taylor expanded in lambda1 around 0 22.0%
Taylor expanded in phi1 around 0 34.9%
if -5.9999999999999995e-25 < phi2 < 8.8000000000000002e-21Initial program 85.0%
Simplified85.0%
Applied egg-rr68.3%
unpow168.3%
Simplified68.3%
Taylor expanded in phi2 around 0 65.2%
Taylor expanded in phi2 around 0 65.2%
Final simplification47.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (* t_1 t_1)))
(if (<= t_1 -0.02)
(*
(atan2
(sqrt (pow t_0 2.0))
(sqrt (- 1.0 (fma t_2 t_3 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
(* 2.0 R))
(if (<= t_1 0.22)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_1 (* t_2 t_1))
(pow (sin (/ (* phi1 (- 1.0 (/ phi2 phi1))) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(*
(* 2.0 R)
(atan2
t_0
(sqrt (- 1.0 (fma t_2 t_3 (pow (sin (* phi1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = t_1 * t_1;
double tmp;
if (t_1 <= -0.02) {
tmp = atan2(sqrt(pow(t_0, 2.0)), sqrt((1.0 - fma(t_2, t_3, pow(sin(((phi1 - phi2) / 2.0)), 2.0))))) * (2.0 * R);
} else if (t_1 <= 0.22) {
tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_2 * t_1)) + pow(sin(((phi1 * (1.0 - (phi2 / phi1))) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = (2.0 * R) * atan2(t_0, sqrt((1.0 - fma(t_2, t_3, pow(sin((phi1 * 0.5)), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = Float64(t_1 * t_1) tmp = 0.0 if (t_1 <= -0.02) tmp = Float64(atan(sqrt((t_0 ^ 2.0)), sqrt(Float64(1.0 - fma(t_2, t_3, (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))) * Float64(2.0 * R)); elseif (t_1 <= 0.22) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_2 * t_1)) + (sin(Float64(Float64(phi1 * Float64(1.0 - Float64(phi2 / phi1))) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = Float64(Float64(2.0 * R) * atan(t_0, sqrt(Float64(1.0 - fma(t_2, t_3, (sin(Float64(phi1 * 0.5)) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t$95$1 * t$95$1), $MachinePrecision]}, If[LessEqual[t$95$1, -0.02], N[(N[ArcTan[N[Sqrt[N[Power[t$95$0, 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * t$95$3 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 0.22], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$2 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 * N[(1.0 - N[(phi2 / phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $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], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(t$95$2 * t$95$3 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := t\_1 \cdot t\_1\\
\mathbf{if}\;t\_1 \leq -0.02:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{{t\_0}^{2}}}{\sqrt{1 - \mathsf{fma}\left(t\_2, t\_3, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)\\
\mathbf{elif}\;t\_1 \leq 0.22:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_2 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 \cdot \left(1 - \frac{\phi_2}{\phi_1}\right)}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \mathsf{fma}\left(t\_2, t\_3, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0200000000000000004Initial program 55.7%
associate-*r*55.7%
*-commutative55.7%
Simplified55.8%
Taylor expanded in phi2 around 0 40.9%
Taylor expanded in phi1 around 0 33.7%
if -0.0200000000000000004 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.220000000000000001Initial program 70.9%
Taylor expanded in phi1 around inf 60.1%
mul-1-neg60.1%
unsub-neg60.1%
Simplified60.1%
Taylor expanded in lambda1 around 0 57.6%
Taylor expanded in lambda2 around 0 56.3%
if 0.220000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 60.8%
associate-*r*60.8%
*-commutative60.8%
Simplified60.8%
Taylor expanded in phi2 around 0 42.9%
Taylor expanded in phi1 around 0 35.6%
Taylor expanded in phi2 around 0 35.8%
*-commutative35.8%
Simplified35.8%
Final simplification42.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (* t_0 t_0)))
(if (<= t_0 -0.15)
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_1 t_2)))
(sqrt (pow (cos (* lambda1 0.5)) 2.0)))))
(if (<= t_0 0.22)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* t_1 t_0))
(pow (sin (/ (* phi1 (- 1.0 (/ phi2 phi1))) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(*
(* 2.0 R)
(atan2
(sin (* 0.5 (- lambda1 lambda2)))
(sqrt (- 1.0 (fma t_1 t_2 (pow (sin (* phi1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = t_0 * t_0;
double tmp;
if (t_0 <= -0.15) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * t_2))), sqrt(pow(cos((lambda1 * 0.5)), 2.0))));
} else if (t_0 <= 0.22) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_0)) + pow(sin(((phi1 * (1.0 - (phi2 / phi1))) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = (2.0 * R) * atan2(sin((0.5 * (lambda1 - lambda2))), sqrt((1.0 - fma(t_1, t_2, pow(sin((phi1 * 0.5)), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = Float64(t_0 * t_0) tmp = 0.0 if (t_0 <= -0.15) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * t_2))), sqrt((cos(Float64(lambda1 * 0.5)) ^ 2.0))))); elseif (t_0 <= 0.22) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_1 * t_0)) + (sin(Float64(Float64(phi1 * Float64(1.0 - Float64(phi2 / phi1))) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = Float64(Float64(2.0 * R) * atan(sin(Float64(0.5 * Float64(lambda1 - lambda2))), sqrt(Float64(1.0 - fma(t_1, t_2, (sin(Float64(phi1 * 0.5)) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$0 * t$95$0), $MachinePrecision]}, If[LessEqual[t$95$0, -0.15], 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$1 * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$0, 0.22], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 * N[(1.0 - N[(phi2 / phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $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], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * t$95$2 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := t\_0 \cdot t\_0\\
\mathbf{if}\;t\_0 \leq -0.15:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot t\_2}}{\sqrt{{\cos \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{elif}\;t\_0 \leq 0.22:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_1 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 \cdot \left(1 - \frac{\phi_2}{\phi_1}\right)}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}{\sqrt{1 - \mathsf{fma}\left(t\_1, t\_2, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.149999999999999994Initial program 54.5%
associate-*l*54.5%
Simplified54.5%
Taylor expanded in phi2 around 0 35.4%
Taylor expanded in lambda2 around 0 29.9%
Taylor expanded in phi1 around 0 31.4%
unpow231.4%
1-sub-sin31.5%
unpow231.5%
Simplified31.5%
if -0.149999999999999994 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.220000000000000001Initial program 70.8%
Taylor expanded in phi1 around inf 60.7%
mul-1-neg60.7%
unsub-neg60.7%
Simplified60.7%
Taylor expanded in lambda1 around 0 57.0%
Taylor expanded in lambda2 around 0 53.6%
if 0.220000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 60.8%
associate-*r*60.8%
*-commutative60.8%
Simplified60.8%
Taylor expanded in phi2 around 0 42.9%
Taylor expanded in phi1 around 0 35.6%
Taylor expanded in phi2 around 0 35.8%
*-commutative35.8%
Simplified35.8%
Final simplification41.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (* t_0 t_0)))
(if (<= t_0 0.28)
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_1 t_2)))
(sqrt (pow (cos (* lambda1 0.5)) 2.0)))))
(*
(* 2.0 R)
(atan2
(sin (* 0.5 (- lambda1 lambda2)))
(sqrt (- 1.0 (fma t_1 t_2 (pow (sin (* phi1 0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = t_0 * t_0;
double tmp;
if (t_0 <= 0.28) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * t_2))), sqrt(pow(cos((lambda1 * 0.5)), 2.0))));
} else {
tmp = (2.0 * R) * atan2(sin((0.5 * (lambda1 - lambda2))), sqrt((1.0 - fma(t_1, t_2, pow(sin((phi1 * 0.5)), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = Float64(t_0 * t_0) tmp = 0.0 if (t_0 <= 0.28) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * t_2))), sqrt((cos(Float64(lambda1 * 0.5)) ^ 2.0))))); else tmp = Float64(Float64(2.0 * R) * atan(sin(Float64(0.5 * Float64(lambda1 - lambda2))), sqrt(Float64(1.0 - fma(t_1, t_2, (sin(Float64(phi1 * 0.5)) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$0 * t$95$0), $MachinePrecision]}, If[LessEqual[t$95$0, 0.28], 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$1 * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * t$95$2 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := t\_0 \cdot t\_0\\
\mathbf{if}\;t\_0 \leq 0.28:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot t\_2}}{\sqrt{{\cos \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}{\sqrt{1 - \mathsf{fma}\left(t\_1, t\_2, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.28000000000000003Initial program 63.3%
associate-*l*63.3%
Simplified63.3%
Taylor expanded in phi2 around 0 43.4%
Taylor expanded in lambda2 around 0 39.4%
Taylor expanded in phi1 around 0 34.7%
unpow234.7%
1-sub-sin34.7%
unpow234.7%
Simplified34.7%
if 0.28000000000000003 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 60.3%
associate-*r*60.3%
*-commutative60.3%
Simplified60.3%
Taylor expanded in phi2 around 0 41.7%
Taylor expanded in phi1 around 0 35.2%
Taylor expanded in phi2 around 0 35.4%
*-commutative35.4%
Simplified35.4%
Final simplification34.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi1 -5e-24) (not (<= phi1 2e-182)))
(*
R
(*
2.0
(atan2
(sin (* (* phi1 0.5) (- 1.0 (/ phi2 phi1))))
(sqrt
(-
1.0
(+
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))))))))
(*
(* 2.0 R)
(atan2
(sin (* 0.5 (- lambda1 lambda2)))
(sqrt
(-
1.0
(fma
(* (cos phi2) (+ 1.0 (* -0.5 (pow phi1 2.0))))
(* t_0 t_0)
(pow (sin (/ (- phi1 phi2) 2.0)) 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 ((phi1 <= -5e-24) || !(phi1 <= 2e-182)) {
tmp = R * (2.0 * atan2(sin(((phi1 * 0.5) * (1.0 - (phi2 / phi1)))), sqrt((1.0 - (pow(sin((0.5 * (phi1 - phi2))), 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))))))));
} else {
tmp = (2.0 * R) * atan2(sin((0.5 * (lambda1 - lambda2))), sqrt((1.0 - fma((cos(phi2) * (1.0 + (-0.5 * pow(phi1, 2.0)))), (t_0 * t_0), pow(sin(((phi1 - phi2) / 2.0)), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi1 <= -5e-24) || !(phi1 <= 2e-182)) tmp = Float64(R * Float64(2.0 * atan(sin(Float64(Float64(phi1 * 0.5) * Float64(1.0 - Float64(phi2 / phi1)))), sqrt(Float64(1.0 - Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))))))))); else tmp = Float64(Float64(2.0 * R) * atan(sin(Float64(0.5 * Float64(lambda1 - lambda2))), sqrt(Float64(1.0 - fma(Float64(cos(phi2) * Float64(1.0 + Float64(-0.5 * (phi1 ^ 2.0)))), Float64(t_0 * t_0), (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -5e-24], N[Not[LessEqual[phi1, 2e-182]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(N[(phi1 * 0.5), $MachinePrecision] * N[(1.0 - N[(phi2 / phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[(1.0 + N[(-0.5 * N[Power[phi1, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $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}\;\phi_1 \leq -5 \cdot 10^{-24} \lor \neg \left(\phi_1 \leq 2 \cdot 10^{-182}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(\left(\phi_1 \cdot 0.5\right) \cdot \left(1 - \frac{\phi_2}{\phi_1}\right)\right)}{\sqrt{1 - \left({\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_2 \cdot \left(1 + -0.5 \cdot {\phi_1}^{2}\right), t\_0 \cdot t\_0, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi1 < -4.9999999999999998e-24 or 2.0000000000000001e-182 < phi1 Initial program 53.1%
Taylor expanded in phi1 around inf 49.3%
mul-1-neg49.3%
unsub-neg49.3%
Simplified49.3%
Taylor expanded in lambda1 around 0 40.2%
Taylor expanded in lambda1 around 0 38.1%
Taylor expanded in lambda2 around 0 19.0%
associate-*r*19.0%
Simplified19.0%
if -4.9999999999999998e-24 < phi1 < 2.0000000000000001e-182Initial program 80.9%
associate-*r*80.9%
*-commutative80.9%
Simplified80.9%
Taylor expanded in phi2 around 0 44.1%
Taylor expanded in phi1 around 0 23.4%
Taylor expanded in phi1 around 0 23.4%
Final simplification20.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2)))))
(if (or (<= phi1 -0.000175) (not (<= phi1 1.6e-184)))
(*
R
(*
2.0
(atan2
(sin (* (* phi1 0.5) (- 1.0 (/ phi2 phi1))))
(sqrt
(-
1.0
(+
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))))))))
(*
(* 2.0 R)
(atan2
t_0
(sqrt
(-
1.0
(+ (* (cos phi2) (pow t_0 2.0)) (pow (sin (* phi2 -0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double tmp;
if ((phi1 <= -0.000175) || !(phi1 <= 1.6e-184)) {
tmp = R * (2.0 * atan2(sin(((phi1 * 0.5) * (1.0 - (phi2 / phi1)))), sqrt((1.0 - (pow(sin((0.5 * (phi1 - phi2))), 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))))))));
} else {
tmp = (2.0 * R) * atan2(t_0, sqrt((1.0 - ((cos(phi2) * pow(t_0, 2.0)) + pow(sin((phi2 * -0.5)), 2.0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: tmp
t_0 = sin((0.5d0 * (lambda1 - lambda2)))
if ((phi1 <= (-0.000175d0)) .or. (.not. (phi1 <= 1.6d-184))) then
tmp = r * (2.0d0 * atan2(sin(((phi1 * 0.5d0) * (1.0d0 - (phi2 / phi1)))), sqrt((1.0d0 - ((sin((0.5d0 * (phi1 - phi2))) ** 2.0d0) + (cos(phi1) * (cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0))))))))
else
tmp = (2.0d0 * r) * atan2(t_0, sqrt((1.0d0 - ((cos(phi2) * (t_0 ** 2.0d0)) + (sin((phi2 * (-0.5d0))) ** 2.0d0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (lambda1 - lambda2)));
double tmp;
if ((phi1 <= -0.000175) || !(phi1 <= 1.6e-184)) {
tmp = R * (2.0 * Math.atan2(Math.sin(((phi1 * 0.5) * (1.0 - (phi2 / phi1)))), Math.sqrt((1.0 - (Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0) + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0))))))));
} else {
tmp = (2.0 * R) * Math.atan2(t_0, Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(t_0, 2.0)) + Math.pow(Math.sin((phi2 * -0.5)), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (lambda1 - lambda2))) tmp = 0 if (phi1 <= -0.000175) or not (phi1 <= 1.6e-184): tmp = R * (2.0 * math.atan2(math.sin(((phi1 * 0.5) * (1.0 - (phi2 / phi1)))), math.sqrt((1.0 - (math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0) + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0)))))))) else: tmp = (2.0 * R) * math.atan2(t_0, math.sqrt((1.0 - ((math.cos(phi2) * math.pow(t_0, 2.0)) + math.pow(math.sin((phi2 * -0.5)), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) tmp = 0.0 if ((phi1 <= -0.000175) || !(phi1 <= 1.6e-184)) tmp = Float64(R * Float64(2.0 * atan(sin(Float64(Float64(phi1 * 0.5) * Float64(1.0 - Float64(phi2 / phi1)))), sqrt(Float64(1.0 - Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))))))))); else tmp = Float64(Float64(2.0 * R) * atan(t_0, sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (t_0 ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))); tmp = 0.0; if ((phi1 <= -0.000175) || ~((phi1 <= 1.6e-184))) tmp = R * (2.0 * atan2(sin(((phi1 * 0.5) * (1.0 - (phi2 / phi1)))), sqrt((1.0 - ((sin((0.5 * (phi1 - phi2))) ^ 2.0) + (cos(phi1) * (cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0)))))))); else tmp = (2.0 * R) * atan2(t_0, sqrt((1.0 - ((cos(phi2) * (t_0 ^ 2.0)) + (sin((phi2 * -0.5)) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -0.000175], N[Not[LessEqual[phi1, 1.6e-184]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(N[(phi1 * 0.5), $MachinePrecision] * N[(1.0 - N[(phi2 / phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
\mathbf{if}\;\phi_1 \leq -0.000175 \lor \neg \left(\phi_1 \leq 1.6 \cdot 10^{-184}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(\left(\phi_1 \cdot 0.5\right) \cdot \left(1 - \frac{\phi_2}{\phi_1}\right)\right)}{\sqrt{1 - \left({\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left(\cos \phi_2 \cdot {t\_0}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi1 < -1.74999999999999998e-4 or 1.6e-184 < phi1 Initial program 53.1%
Taylor expanded in phi1 around inf 49.3%
mul-1-neg49.3%
unsub-neg49.3%
Simplified49.3%
Taylor expanded in lambda1 around 0 40.2%
Taylor expanded in lambda1 around 0 38.1%
Taylor expanded in lambda2 around 0 19.0%
associate-*r*19.0%
Simplified19.0%
if -1.74999999999999998e-4 < phi1 < 1.6e-184Initial program 80.9%
associate-*r*80.9%
*-commutative80.9%
Simplified80.9%
Taylor expanded in phi2 around 0 44.1%
Taylor expanded in phi1 around 0 23.4%
Taylor expanded in phi1 around 0 23.4%
Final simplification20.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2)))))
(*
(* 2.0 R)
(atan2
t_0
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow t_0 2.0)))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
return (2.0 * R) * atan2(t_0, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(t_0, 2.0))) + pow(sin((0.5 * (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
t_0 = sin((0.5d0 * (lambda1 - lambda2)))
code = (2.0d0 * r) * atan2(t_0, sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (t_0 ** 2.0d0))) + (sin((0.5d0 * (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((0.5 * (lambda1 - lambda2)));
return (2.0 * R) * Math.atan2(t_0, Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(t_0, 2.0))) + Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (lambda1 - lambda2))) return (2.0 * R) * math.atan2(t_0, math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(t_0, 2.0))) + math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) return Float64(Float64(2.0 * R) * atan(t_0, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (t_0 ^ 2.0))) + (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))); tmp = (2.0 * R) * atan2(t_0, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (t_0 ^ 2.0))) + (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {t\_0}^{2}\right) + {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.4%
associate-*r*62.4%
*-commutative62.4%
Simplified62.4%
Taylor expanded in phi2 around 0 42.4%
Taylor expanded in phi1 around 0 14.7%
Taylor expanded in lambda1 around 0 14.7%
Final simplification14.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2)))))
(*
(* 2.0 R)
(atan2
t_0
(sqrt
(-
1.0
(+ (* (cos phi2) (pow t_0 2.0)) (pow (sin (* phi2 -0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
return (2.0 * R) * atan2(t_0, sqrt((1.0 - ((cos(phi2) * pow(t_0, 2.0)) + pow(sin((phi2 * -0.5)), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (lambda1 - lambda2)))
code = (2.0d0 * r) * atan2(t_0, sqrt((1.0d0 - ((cos(phi2) * (t_0 ** 2.0d0)) + (sin((phi2 * (-0.5d0))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (lambda1 - lambda2)));
return (2.0 * R) * Math.atan2(t_0, Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(t_0, 2.0)) + Math.pow(Math.sin((phi2 * -0.5)), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (lambda1 - lambda2))) return (2.0 * R) * math.atan2(t_0, math.sqrt((1.0 - ((math.cos(phi2) * math.pow(t_0, 2.0)) + math.pow(math.sin((phi2 * -0.5)), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) return Float64(Float64(2.0 * R) * atan(t_0, sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (t_0 ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))); tmp = (2.0 * R) * atan2(t_0, sqrt((1.0 - ((cos(phi2) * (t_0 ^ 2.0)) + (sin((phi2 * -0.5)) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left(\cos \phi_2 \cdot {t\_0}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.4%
associate-*r*62.4%
*-commutative62.4%
Simplified62.4%
Taylor expanded in phi2 around 0 42.4%
Taylor expanded in phi1 around 0 14.7%
Taylor expanded in phi1 around 0 14.6%
Final simplification14.6%
herbie shell --seed 2024144
(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))))))))))