
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 22 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 phi2)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_2 (* (* (cos phi1) (cos phi2)) t_2))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(+
(fma (cos (* 0.5 phi2)) (sin (* 0.5 phi1)) (* t_0 (- t_1)))
(fma (- t_0) t_1 (* t_0 t_1)))
2.0)
t_3))
(sqrt
(-
1.0
(+
t_3
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * phi2));
double t_1 = cos((0.5 * phi1));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * ((cos(phi1) * cos(phi2)) * t_2);
return R * (2.0 * atan2(sqrt((pow((fma(cos((0.5 * phi2)), sin((0.5 * phi1)), (t_0 * -t_1)) + fma(-t_0, t_1, (t_0 * t_1))), 2.0) + t_3)), sqrt((1.0 - (t_3 + pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi2)) t_1 = cos(Float64(0.5 * phi1)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_2 * Float64(Float64(cos(phi1) * cos(phi2)) * t_2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(fma(cos(Float64(0.5 * phi2)), sin(Float64(0.5 * phi1)), Float64(t_0 * Float64(-t_1))) + fma(Float64(-t_0), t_1, Float64(t_0 * t_1))) ^ 2.0) + t_3)), sqrt(Float64(1.0 - Float64(t_3 + (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))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(t$95$0 * (-t$95$1)), $MachinePrecision]), $MachinePrecision] + N[((-t$95$0) * t$95$1 + N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 + 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]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \phi_2\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_2 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(0.5 \cdot \phi_2\right), \sin \left(0.5 \cdot \phi_1\right), t\_0 \cdot \left(-t\_1\right)\right) + \mathsf{fma}\left(-t\_0, t\_1, t\_0 \cdot t\_1\right)\right)}^{2} + t\_3}}{\sqrt{1 - \left(t\_3 + {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
div-sub62.4%
sin-diff63.4%
Applied egg-rr63.4%
div-sub62.4%
sin-diff63.4%
Applied egg-rr77.1%
fma-neg77.1%
distribute-rgt-neg-in77.1%
Simplified77.1%
distribute-rgt-neg-out77.1%
fma-neg77.1%
*-un-lft-identity77.1%
prod-diff77.1%
Applied egg-rr77.1%
Simplified77.1%
Final simplification77.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_2 (* t_0 t_2)))
(t_4 (+ t_3 t_1))
(t_5 (sqrt (- 1.0 t_4))))
(if (<= (atan2 (sqrt t_4) t_5) 0.085)
(*
R
(*
2.0
(atan2
(sqrt
(+
t_1
(*
t_2
(*
t_0
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))))))
t_5)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* 0.5 phi1)))
(* (sin (* 0.5 phi2)) (cos (* 0.5 phi1))))
2.0)
(*
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))))))
(sqrt
(-
1.0
(+
t_3
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * (t_0 * t_2);
double t_4 = t_3 + t_1;
double t_5 = sqrt((1.0 - t_4));
double tmp;
if (atan2(sqrt(t_4), t_5) <= 0.085) {
tmp = R * (2.0 * atan2(sqrt((t_1 + (t_2 * (t_0 * ((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))))))), t_5));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * sin((0.5 * phi1))) - (sin((0.5 * phi2)) * cos((0.5 * phi1)))), 2.0) + (cos(phi1) * (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))), sqrt((1.0 - (t_3 + pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: t_5
real(8) :: tmp
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = t_2 * (t_0 * t_2)
t_4 = t_3 + t_1
t_5 = sqrt((1.0d0 - t_4))
if (atan2(sqrt(t_4), t_5) <= 0.085d0) then
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (t_2 * (t_0 * ((sin((lambda1 / 2.0d0)) * cos((lambda2 / 2.0d0))) - (cos((lambda1 / 2.0d0)) * sin((lambda2 / 2.0d0)))))))), t_5))
else
tmp = r * (2.0d0 * atan2(sqrt(((((cos((0.5d0 * phi2)) * sin((0.5d0 * phi1))) - (sin((0.5d0 * phi2)) * cos((0.5d0 * phi1)))) ** 2.0d0) + (cos(phi1) * (cos(phi2) * (0.5d0 + ((-0.5d0) * cos((lambda1 - lambda2)))))))), sqrt((1.0d0 - (t_3 + (((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * (t_0 * t_2);
double t_4 = t_3 + t_1;
double t_5 = Math.sqrt((1.0 - t_4));
double tmp;
if (Math.atan2(Math.sqrt(t_4), t_5) <= 0.085) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_2 * (t_0 * ((Math.sin((lambda1 / 2.0)) * Math.cos((lambda2 / 2.0))) - (Math.cos((lambda1 / 2.0)) * Math.sin((lambda2 / 2.0)))))))), t_5));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((0.5 * phi1))) - (Math.sin((0.5 * phi2)) * Math.cos((0.5 * phi1)))), 2.0) + (Math.cos(phi1) * (Math.cos(phi2) * (0.5 + (-0.5 * Math.cos((lambda1 - lambda2)))))))), Math.sqrt((1.0 - (t_3 + Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = t_2 * (t_0 * t_2) t_4 = t_3 + t_1 t_5 = math.sqrt((1.0 - t_4)) tmp = 0 if math.atan2(math.sqrt(t_4), t_5) <= 0.085: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + (t_2 * (t_0 * ((math.sin((lambda1 / 2.0)) * math.cos((lambda2 / 2.0))) - (math.cos((lambda1 / 2.0)) * math.sin((lambda2 / 2.0)))))))), t_5)) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(((math.cos((0.5 * phi2)) * math.sin((0.5 * phi1))) - (math.sin((0.5 * phi2)) * math.cos((0.5 * phi1)))), 2.0) + (math.cos(phi1) * (math.cos(phi2) * (0.5 + (-0.5 * math.cos((lambda1 - lambda2)))))))), math.sqrt((1.0 - (t_3 + math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_2 * Float64(t_0 * t_2)) t_4 = Float64(t_3 + t_1) t_5 = sqrt(Float64(1.0 - t_4)) tmp = 0.0 if (atan(sqrt(t_4), t_5) <= 0.085) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_2 * Float64(t_0 * Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))))))), t_5))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(0.5 * phi1))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(0.5 * phi1)))) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))))))), sqrt(Float64(1.0 - Float64(t_3 + (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))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = t_2 * (t_0 * t_2); t_4 = t_3 + t_1; t_5 = sqrt((1.0 - t_4)); tmp = 0.0; if (atan2(sqrt(t_4), t_5) <= 0.085) tmp = R * (2.0 * atan2(sqrt((t_1 + (t_2 * (t_0 * ((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))))))), t_5)); else tmp = R * (2.0 * atan2(sqrt(((((cos((0.5 * phi2)) * sin((0.5 * phi1))) - (sin((0.5 * phi2)) * cos((0.5 * phi1)))) ^ 2.0) + (cos(phi1) * (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))), sqrt((1.0 - (t_3 + (((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 * N[(t$95$0 * t$95$2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(t$95$3 + t$95$1), $MachinePrecision]}, Block[{t$95$5 = N[Sqrt[N[(1.0 - t$95$4), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[ArcTan[N[Sqrt[t$95$4], $MachinePrecision] / t$95$5], $MachinePrecision], 0.085], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$2 * N[(t$95$0 * 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]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$5], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 + 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]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_2 \cdot \left(t\_0 \cdot t\_2\right)\\
t_4 := t\_3 + t\_1\\
t_5 := \sqrt{1 - t\_4}\\
\mathbf{if}\;\tan^{-1}_* \frac{\sqrt{t\_4}}{t\_5} \leq 0.085:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_2 \cdot \left(t\_0 \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)\right)}}{t\_5}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(0.5 \cdot \phi_1\right) - \sin \left(0.5 \cdot \phi_2\right) \cdot \cos \left(0.5 \cdot \phi_1\right)\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\right)}}{\sqrt{1 - \left(t\_3 + {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\right)}}\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)))))))) < 0.0850000000000000061Initial program 94.7%
div-sub94.7%
sin-diff94.8%
Applied egg-rr94.8%
if 0.0850000000000000061 < (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) Initial program 60.1%
div-sub60.1%
sin-diff61.2%
Applied egg-rr61.2%
div-sub60.1%
sin-diff61.2%
Applied egg-rr75.9%
fma-neg75.9%
distribute-rgt-neg-in75.9%
Simplified75.9%
distribute-rgt-neg-out75.9%
fma-neg75.9%
*-un-lft-identity75.9%
prod-diff75.9%
Applied egg-rr75.9%
Simplified75.9%
Applied egg-rr58.1%
Simplified75.9%
Final simplification77.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (/ phi1 2.0)))
(t_1 (sin (/ phi1 2.0)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (sin (/ phi2 2.0)))
(t_4 (* t_2 (* (* (cos phi1) (cos phi2)) t_2)))
(t_5 (cos (/ phi2 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_4 (pow (fma t_1 t_5 (* t_3 (- t_0))) 2.0)))
(sqrt (- 1.0 (+ t_4 (pow (- (* t_1 t_5) (* t_0 t_3)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 / 2.0));
double t_1 = sin((phi1 / 2.0));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = sin((phi2 / 2.0));
double t_4 = t_2 * ((cos(phi1) * cos(phi2)) * t_2);
double t_5 = cos((phi2 / 2.0));
return R * (2.0 * atan2(sqrt((t_4 + pow(fma(t_1, t_5, (t_3 * -t_0)), 2.0))), sqrt((1.0 - (t_4 + pow(((t_1 * t_5) - (t_0 * t_3)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 / 2.0)) t_1 = sin(Float64(phi1 / 2.0)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = sin(Float64(phi2 / 2.0)) t_4 = Float64(t_2 * Float64(Float64(cos(phi1) * cos(phi2)) * t_2)) t_5 = cos(Float64(phi2 / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + (fma(t_1, t_5, Float64(t_3 * Float64(-t_0))) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_4 + (Float64(Float64(t_1 * t_5) - Float64(t_0 * t_3)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$2 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + N[Power[N[(t$95$1 * t$95$5 + N[(t$95$3 * (-t$95$0)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$4 + N[Power[N[(N[(t$95$1 * t$95$5), $MachinePrecision] - N[(t$95$0 * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\frac{\phi_1}{2}\right)\\
t_1 := \sin \left(\frac{\phi_1}{2}\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \sin \left(\frac{\phi_2}{2}\right)\\
t_4 := t\_2 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2\right)\\
t_5 := \cos \left(\frac{\phi_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + {\left(\mathsf{fma}\left(t\_1, t\_5, t\_3 \cdot \left(-t\_0\right)\right)\right)}^{2}}}{\sqrt{1 - \left(t\_4 + {\left(t\_1 \cdot t\_5 - t\_0 \cdot t\_3\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
div-sub62.4%
sin-diff63.4%
Applied egg-rr63.4%
div-sub62.4%
sin-diff63.4%
Applied egg-rr77.1%
fma-neg77.1%
distribute-rgt-neg-in77.1%
Simplified77.1%
Final simplification77.1%
(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))
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))))
(* 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 = (t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0);
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 = (t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0)
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 = (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0);
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 = (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0)) 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 = (t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0); 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[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + 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]}, 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 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\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}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.4%
div-sub62.4%
sin-diff63.4%
Applied egg-rr63.4%
div-sub62.4%
sin-diff63.4%
Applied egg-rr77.1%
Final simplification77.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_2 (* (cos phi1) (cos phi2)))
(t_3
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))
(t_4 (* t_0 t_0))
(t_5 (* t_2 t_4)))
(if (<= (- lambda1 lambda2) -0.02)
(* R (* 2.0 (atan2 (sqrt (+ t_3 t_5)) (sqrt (- (- 1.0 t_1) t_5)))))
(if (<= (- lambda1 lambda2) 2e+52)
(*
R
(*
2.0
(atan2
(hypot
(-
(* (cos (* 0.5 phi2)) (sin (* 0.5 phi1)))
(* (sin (* 0.5 phi2)) (cos (* 0.5 phi1))))
(sqrt
(*
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))))))
(sqrt (- 1.0 (+ (* t_0 (* t_2 t_0)) t_3))))))
(*
(atan2
(sqrt (fma t_2 t_4 t_1))
(sqrt
(-
1.0
(fma
t_2
(-
0.5
(/
(+
(* (cos lambda1) (cos lambda2))
(* (sin lambda1) (sin lambda2)))
2.0))
t_1))))
(* R 2.0))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = cos(phi1) * cos(phi2);
double t_3 = pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0);
double t_4 = t_0 * t_0;
double t_5 = t_2 * t_4;
double tmp;
if ((lambda1 - lambda2) <= -0.02) {
tmp = R * (2.0 * atan2(sqrt((t_3 + t_5)), sqrt(((1.0 - t_1) - t_5))));
} else if ((lambda1 - lambda2) <= 2e+52) {
tmp = R * (2.0 * atan2(hypot(((cos((0.5 * phi2)) * sin((0.5 * phi1))) - (sin((0.5 * phi2)) * cos((0.5 * phi1)))), sqrt((cos(phi1) * (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))), sqrt((1.0 - ((t_0 * (t_2 * t_0)) + t_3)))));
} else {
tmp = atan2(sqrt(fma(t_2, t_4, t_1)), sqrt((1.0 - fma(t_2, (0.5 - (((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0)), t_1)))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0 t_4 = Float64(t_0 * t_0) t_5 = Float64(t_2 * t_4) tmp = 0.0 if (Float64(lambda1 - lambda2) <= -0.02) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + t_5)), sqrt(Float64(Float64(1.0 - t_1) - t_5))))); elseif (Float64(lambda1 - lambda2) <= 2e+52) tmp = Float64(R * Float64(2.0 * atan(hypot(Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(0.5 * phi1))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(0.5 * phi1)))), sqrt(Float64(cos(phi1) * Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))))))), sqrt(Float64(1.0 - Float64(Float64(t_0 * Float64(t_2 * t_0)) + t_3)))))); else tmp = Float64(atan(sqrt(fma(t_2, t_4, t_1)), sqrt(Float64(1.0 - fma(t_2, Float64(0.5 - Float64(Float64(Float64(cos(lambda1) * cos(lambda2)) + Float64(sin(lambda1) * sin(lambda2))) / 2.0)), t_1)))) * Float64(R * 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[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$0 * t$95$0), $MachinePrecision]}, Block[{t$95$5 = N[(t$95$2 * t$95$4), $MachinePrecision]}, If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -0.02], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + t$95$5), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] - t$95$5), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 2e+52], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] ^ 2 + N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$0 * N[(t$95$2 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[(t$95$2 * t$95$4 + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(0.5 - N[(N[(N[(N[Cos[lambda1], $MachinePrecision] * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[lambda1], $MachinePrecision] * N[Sin[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\\
t_4 := t\_0 \cdot t\_0\\
t_5 := t\_2 \cdot t\_4\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -0.02:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + t\_5}}{\sqrt{\left(1 - t\_1\right) - t\_5}}\right)\\
\mathbf{elif}\;\lambda_1 - \lambda_2 \leq 2 \cdot 10^{+52}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(0.5 \cdot \phi_1\right) - \sin \left(0.5 \cdot \phi_2\right) \cdot \cos \left(0.5 \cdot \phi_1\right), \sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\right)}\right)}{\sqrt{1 - \left(t\_0 \cdot \left(t\_2 \cdot t\_0\right) + t\_3\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, t\_4, t\_1\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_2, 0.5 - \frac{\cos \lambda_1 \cdot \cos \lambda_2 + \sin \lambda_1 \cdot \sin \lambda_2}{2}, t\_1\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -0.0200000000000000004Initial program 55.4%
associate-*l*55.4%
Simplified55.4%
div-sub55.4%
sin-diff56.4%
Applied egg-rr56.6%
if -0.0200000000000000004 < (-.f64 lambda1 lambda2) < 2e52Initial program 72.1%
div-sub72.1%
sin-diff73.3%
Applied egg-rr73.3%
div-sub72.1%
sin-diff73.3%
Applied egg-rr95.7%
fma-neg95.7%
distribute-rgt-neg-in95.7%
Simplified95.7%
distribute-rgt-neg-out95.7%
fma-neg95.7%
*-un-lft-identity95.7%
prod-diff95.7%
Applied egg-rr95.7%
Simplified95.7%
Applied egg-rr87.3%
Simplified87.3%
if 2e52 < (-.f64 lambda1 lambda2) Initial program 60.8%
associate-*r*60.8%
*-commutative60.8%
Simplified60.7%
sin-mult60.8%
div-inv60.8%
metadata-eval60.8%
div-inv60.8%
metadata-eval60.8%
cos-sum60.9%
cos-260.8%
div-inv60.8%
metadata-eval60.8%
Applied egg-rr60.8%
div-sub60.8%
+-inverses60.8%
+-inverses60.8%
+-inverses60.8%
cos-060.8%
metadata-eval60.8%
*-commutative60.8%
Simplified60.8%
associate-*r*60.8%
metadata-eval60.8%
*-un-lft-identity60.8%
cos-diff61.9%
Applied egg-rr61.9%
Final simplification67.9%
(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 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(+
t_1
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ 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 t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (t_1 + pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
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 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (t_1 + (((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - (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))))));
}
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 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - (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))))))
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 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - 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))))))) 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 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (t_1 + (((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(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[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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]], $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 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \left(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}\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
div-sub62.4%
sin-diff63.4%
Applied egg-rr63.4%
Final simplification63.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2))) (t_1 (* 0.5 (- lambda1 lambda2))))
(*
(* R 2.0)
(atan2
(sqrt
(fabs
(fma (pow (sin t_1) 2.0) t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))
(sqrt
(-
1.0
(fma
t_0
(- 0.5 (/ (cos (* 2.0 t_1)) 2.0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = 0.5 * (lambda1 - lambda2);
return (R * 2.0) * atan2(sqrt(fabs(fma(pow(sin(t_1), 2.0), t_0, pow(sin((0.5 * (phi1 - phi2))), 2.0)))), sqrt((1.0 - fma(t_0, (0.5 - (cos((2.0 * t_1)) / 2.0)), pow(sin(((phi1 - phi2) / 2.0)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(0.5 * Float64(lambda1 - lambda2)) return Float64(Float64(R * 2.0) * atan(sqrt(abs(fma((sin(t_1) ^ 2.0), t_0, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))), sqrt(Float64(1.0 - fma(t_0, Float64(0.5 - Float64(cos(Float64(2.0 * t_1)) / 2.0)), (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)))))) 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[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]}, N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Abs[N[(N[Power[N[Sin[t$95$1], $MachinePrecision], 2.0], $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[(0.5 - N[(N[Cos[N[(2.0 * t$95$1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $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 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := 0.5 \cdot \left(\lambda_1 - \lambda_2\right)\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{\left|\mathsf{fma}\left({\sin t\_1}^{2}, t\_0, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}{\sqrt{1 - \mathsf{fma}\left(t\_0, 0.5 - \frac{\cos \left(2 \cdot t\_1\right)}{2}, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.4%
associate-*r*62.4%
*-commutative62.4%
Simplified62.4%
sin-mult62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
cos-sum62.4%
cos-262.4%
div-inv62.4%
metadata-eval62.4%
Applied egg-rr62.4%
div-sub62.4%
+-inverses62.4%
+-inverses62.4%
+-inverses62.4%
cos-062.4%
metadata-eval62.4%
*-commutative62.4%
Simplified62.4%
add-sqr-sqrt62.4%
pow1/262.4%
pow1/262.4%
pow-prod-down61.6%
Applied egg-rr61.6%
unpow1/261.6%
unpow261.6%
rem-sqrt-square62.7%
*-commutative62.7%
*-commutative62.7%
Simplified62.7%
Final simplification62.7%
(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 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt (- (+ 1.0 (- (/ (cos (- phi1 phi2)) 2.0) 0.5)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt(((1.0d0 + ((cos((phi1 - phi2)) / 2.0d0) - 0.5d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt(((1.0 + ((Math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt(((1.0 + ((math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(Float64(1.0 + Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{\left(1 + \left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right)\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
unpow262.4%
sin-mult62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
Applied egg-rr62.4%
div-sub62.4%
+-inverses62.4%
cos-062.4%
metadata-eval62.4%
distribute-lft-out62.4%
metadata-eval62.4%
*-rgt-identity62.4%
Simplified62.4%
Final simplification62.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_0 (* t_1 t_1))))
(sqrt
(+
(- 1.0 t_2)
(*
t_0
(- (/ (cos (* 2.0 (* 0.5 (- lambda1 lambda2)))) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - t_2) + (t_0 * ((cos((2.0 * (0.5 * (lambda1 - lambda2)))) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0d0 - t_2) + (t_0 * ((cos((2.0d0 * (0.5d0 * (lambda1 - lambda2)))) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((t_2 + (t_0 * (t_1 * t_1)))), Math.sqrt(((1.0 - t_2) + (t_0 * ((Math.cos((2.0 * (0.5 * (lambda1 - lambda2)))) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) return R * (2.0 * math.atan2(math.sqrt((t_2 + (t_0 * (t_1 * t_1)))), math.sqrt(((1.0 - t_2) + (t_0 * ((math.cos((2.0 * (0.5 * (lambda1 - lambda2)))) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_0 * Float64(t_1 * t_1)))), sqrt(Float64(Float64(1.0 - t_2) + Float64(t_0 * Float64(Float64(cos(Float64(2.0 * Float64(0.5 * Float64(lambda1 - lambda2)))) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = R * (2.0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - t_2) + (t_0 * ((cos((2.0 * (0.5 * (lambda1 - lambda2)))) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$2), $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[N[(2.0 * N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left(1 - t\_2\right) + t\_0 \cdot \left(\frac{\cos \left(2 \cdot \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
sin-mult62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
cos-sum62.4%
cos-262.4%
div-inv62.4%
metadata-eval62.4%
Applied egg-rr62.4%
div-sub62.4%
+-inverses62.4%
+-inverses62.4%
+-inverses62.4%
cos-062.4%
metadata-eval62.4%
*-commutative62.4%
Simplified62.4%
Final simplification62.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* 0.5 (- lambda1 lambda2)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (or (<= phi2 -5e-9) (not (<= phi2 3e-7)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* t_2 t_0)) t_3))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))
(pow (sin (* 0.5 phi2)) 2.0)))))))
(*
(* R 2.0)
(atan2
(sqrt
(+ (* (cos phi1) (pow (sin t_1) 2.0)) (pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- 1.0 (fma t_2 (- 0.5 (/ (cos (* 2.0 t_1)) 2.0)) t_3))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = 0.5 * (lambda1 - lambda2);
double t_2 = cos(phi1) * cos(phi2);
double t_3 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi2 <= -5e-9) || !(phi2 <= 3e-7)) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_2 * t_0)) + t_3)), sqrt((1.0 - ((cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0)) + pow(sin((0.5 * phi2)), 2.0))))));
} else {
tmp = (R * 2.0) * atan2(sqrt(((cos(phi1) * pow(sin(t_1), 2.0)) + pow(sin((0.5 * phi1)), 2.0))), sqrt((1.0 - fma(t_2, (0.5 - (cos((2.0 * t_1)) / 2.0)), t_3))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(0.5 * Float64(lambda1 - lambda2)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if ((phi2 <= -5e-9) || !(phi2 <= 3e-7)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_2 * t_0)) + t_3)), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0)) + (sin(Float64(0.5 * phi2)) ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(Float64(cos(phi1) * (sin(t_1) ^ 2.0)) + (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_2, Float64(0.5 - Float64(cos(Float64(2.0 * t_1)) / 2.0)), t_3))))); 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[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -5e-9], N[Not[LessEqual[phi2, 3e-7]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$2 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[t$95$1], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(0.5 - N[(N[Cos[N[(2.0 * t$95$1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := 0.5 \cdot \left(\lambda_1 - \lambda_2\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -5 \cdot 10^{-9} \lor \neg \left(\phi_2 \leq 3 \cdot 10^{-7}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_2 \cdot t\_0\right) + t\_3}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2} + {\sin \left(0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin t\_1}^{2} + {\sin \left(0.5 \cdot \phi_1\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(t\_2, 0.5 - \frac{\cos \left(2 \cdot t\_1\right)}{2}, t\_3\right)}}\\
\end{array}
\end{array}
if phi2 < -5.0000000000000001e-9 or 2.9999999999999999e-7 < phi2 Initial program 51.1%
div-sub51.1%
sin-diff53.1%
Applied egg-rr53.1%
Taylor expanded in lambda1 around 0 42.2%
Taylor expanded in phi1 around 0 41.2%
if -5.0000000000000001e-9 < phi2 < 2.9999999999999999e-7Initial program 75.1%
associate-*r*75.1%
*-commutative75.1%
Simplified75.1%
sin-mult75.2%
div-inv75.2%
metadata-eval75.2%
div-inv75.2%
metadata-eval75.2%
cos-sum75.2%
cos-275.2%
div-inv75.2%
metadata-eval75.2%
Applied egg-rr75.2%
div-sub75.2%
+-inverses75.2%
+-inverses75.2%
+-inverses75.2%
cos-075.2%
metadata-eval75.2%
*-commutative75.2%
Simplified75.2%
Taylor expanded in phi2 around 0 73.6%
Final simplification56.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -8.5e-9) (not (<= phi2 4.1e-7)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* t_1 t_0)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))
(pow (sin (* 0.5 phi2)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_0)) (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt
(-
1.0
(+
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* 0.5 phi1)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -8.5e-9) || !(phi2 <= 4.1e-7)) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - ((cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0)) + pow(sin((0.5 * phi2)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + pow(sin((phi1 / 2.0)), 2.0))), sqrt((1.0 - ((cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + pow(sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
if ((phi2 <= (-8.5d-9)) .or. (.not. (phi2 <= 4.1d-7))) then
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * (t_1 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - ((cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0)) + (sin((0.5d0 * phi2)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin((phi1 / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - ((cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (sin((0.5d0 * phi1)) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double tmp;
if ((phi2 <= -8.5e-9) || !(phi2 <= 4.1e-7)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_1 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0)) + Math.pow(Math.sin((0.5 * phi2)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_1 * (t_0 * t_0)) + Math.pow(Math.sin((phi1 / 2.0)), 2.0))), Math.sqrt((1.0 - ((Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + Math.pow(Math.sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) tmp = 0 if (phi2 <= -8.5e-9) or not (phi2 <= 4.1e-7): tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * (t_1 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - ((math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0)) + math.pow(math.sin((0.5 * phi2)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((t_1 * (t_0 * t_0)) + math.pow(math.sin((phi1 / 2.0)), 2.0))), math.sqrt((1.0 - ((math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + math.pow(math.sin((0.5 * phi1)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -8.5e-9) || !(phi2 <= 4.1e-7)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_1 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0)) + (sin(Float64(0.5 * phi2)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_0)) + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); tmp = 0.0; if ((phi2 <= -8.5e-9) || ~((phi2 <= 4.1e-7))) tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - ((cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0)) + (sin((0.5 * phi2)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin((phi1 / 2.0)) ^ 2.0))), sqrt((1.0 - ((cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + (sin((0.5 * phi1)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -8.5e-9], N[Not[LessEqual[phi2, 4.1e-7]], $MachinePrecision]], 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 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -8.5 \cdot 10^{-9} \lor \neg \left(\phi_2 \leq 4.1 \cdot 10^{-7}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_1 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2} + {\sin \left(0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -8.5e-9 or 4.0999999999999999e-7 < phi2 Initial program 51.1%
div-sub51.1%
sin-diff53.1%
Applied egg-rr53.1%
Taylor expanded in lambda1 around 0 42.2%
Taylor expanded in phi1 around 0 41.2%
if -8.5e-9 < phi2 < 4.0999999999999999e-7Initial program 75.1%
associate-*l*75.1%
Simplified75.1%
Taylor expanded in phi2 around 0 75.1%
Taylor expanded in phi1 around inf 73.5%
Final simplification56.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi2 -9.5e-9) (not (<= phi2 3.1e-5)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* t_1 t_0) (sin (* lambda2 -0.5)))))
(sqrt (- 1.0 (+ (* (cos phi2) t_2) (pow (sin (* phi2 -0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_0)) (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt
(- 1.0 (+ (* (cos phi1) t_2) (pow (sin (* 0.5 phi1)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi2 <= -9.5e-9) || !(phi2 <= 3.1e-5)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_1 * t_0) * sin((lambda2 * -0.5))))), sqrt((1.0 - ((cos(phi2) * t_2) + pow(sin((phi2 * -0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + pow(sin((phi1 / 2.0)), 2.0))), sqrt((1.0 - ((cos(phi1) * t_2) + pow(sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
t_2 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
if ((phi2 <= (-9.5d-9)) .or. (.not. (phi2 <= 3.1d-5))) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((t_1 * t_0) * sin((lambda2 * (-0.5d0)))))), sqrt((1.0d0 - ((cos(phi2) * t_2) + (sin((phi2 * (-0.5d0))) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin((phi1 / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - ((cos(phi1) * t_2) + (sin((0.5d0 * phi1)) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double t_2 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi2 <= -9.5e-9) || !(phi2 <= 3.1e-5)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_1 * t_0) * Math.sin((lambda2 * -0.5))))), Math.sqrt((1.0 - ((Math.cos(phi2) * t_2) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_1 * (t_0 * t_0)) + Math.pow(Math.sin((phi1 / 2.0)), 2.0))), Math.sqrt((1.0 - ((Math.cos(phi1) * t_2) + Math.pow(Math.sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) t_2 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) tmp = 0 if (phi2 <= -9.5e-9) or not (phi2 <= 3.1e-5): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_1 * t_0) * math.sin((lambda2 * -0.5))))), math.sqrt((1.0 - ((math.cos(phi2) * t_2) + math.pow(math.sin((phi2 * -0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((t_1 * (t_0 * t_0)) + math.pow(math.sin((phi1 / 2.0)), 2.0))), math.sqrt((1.0 - ((math.cos(phi1) * t_2) + math.pow(math.sin((0.5 * phi1)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi2 <= -9.5e-9) || !(phi2 <= 3.1e-5)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_1 * t_0) * sin(Float64(lambda2 * -0.5))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_2) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_0)) + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_2) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); t_2 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; tmp = 0.0; if ((phi2 <= -9.5e-9) || ~((phi2 <= 3.1e-5))) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((t_1 * t_0) * sin((lambda2 * -0.5))))), sqrt((1.0 - ((cos(phi2) * t_2) + (sin((phi2 * -0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin((phi1 / 2.0)) ^ 2.0))), sqrt((1.0 - ((cos(phi1) * t_2) + (sin((0.5 * phi1)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -9.5e-9], N[Not[LessEqual[phi2, 3.1e-5]], $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[(t$95$1 * t$95$0), $MachinePrecision] * N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -9.5 \cdot 10^{-9} \lor \neg \left(\phi_2 \leq 3.1 \cdot 10^{-5}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_1 \cdot t\_0\right) \cdot \sin \left(\lambda_2 \cdot -0.5\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_2 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -9.5000000000000007e-9 or 3.10000000000000014e-5 < phi2 Initial program 51.1%
Taylor expanded in lambda1 around 0 40.0%
Taylor expanded in phi1 around 0 41.0%
if -9.5000000000000007e-9 < phi2 < 3.10000000000000014e-5Initial program 75.1%
associate-*l*75.1%
Simplified75.1%
Taylor expanded in phi2 around 0 75.1%
Taylor expanded in phi1 around inf 73.5%
Final simplification56.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (* 0.5 (- lambda1 lambda2)))
(t_2 (pow (sin t_1) 2.0))
(t_3
(sqrt
(-
1.0
(fma
t_0
(- 0.5 (/ (cos (* 2.0 t_1)) 2.0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
(t_4 (sin (/ (- lambda1 lambda2) 2.0)))
(t_5 (+ (* (cos phi1) t_2) (pow (sin (* 0.5 phi1)) 2.0))))
(if (<= phi1 -0.035)
(* (* R 2.0) (atan2 (sqrt t_5) t_3))
(if (<= phi1 0.0066)
(*
(* R 2.0)
(atan2
(sqrt (+ (* (cos phi2) t_2) (pow (sin (* phi2 -0.5)) 2.0)))
t_3))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* t_4 t_4)) (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt (- 1.0 t_5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = 0.5 * (lambda1 - lambda2);
double t_2 = pow(sin(t_1), 2.0);
double t_3 = sqrt((1.0 - fma(t_0, (0.5 - (cos((2.0 * t_1)) / 2.0)), pow(sin(((phi1 - phi2) / 2.0)), 2.0))));
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double t_5 = (cos(phi1) * t_2) + pow(sin((0.5 * phi1)), 2.0);
double tmp;
if (phi1 <= -0.035) {
tmp = (R * 2.0) * atan2(sqrt(t_5), t_3);
} else if (phi1 <= 0.0066) {
tmp = (R * 2.0) * atan2(sqrt(((cos(phi2) * t_2) + pow(sin((phi2 * -0.5)), 2.0))), t_3);
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_4 * t_4)) + pow(sin((phi1 / 2.0)), 2.0))), sqrt((1.0 - t_5))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(0.5 * Float64(lambda1 - lambda2)) t_2 = sin(t_1) ^ 2.0 t_3 = sqrt(Float64(1.0 - fma(t_0, Float64(0.5 - Float64(cos(Float64(2.0 * t_1)) / 2.0)), (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)))) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_5 = Float64(Float64(cos(phi1) * t_2) + (sin(Float64(0.5 * phi1)) ^ 2.0)) tmp = 0.0 if (phi1 <= -0.035) tmp = Float64(Float64(R * 2.0) * atan(sqrt(t_5), t_3)); elseif (phi1 <= 0.0066) tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(Float64(cos(phi2) * t_2) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), t_3)); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_4 * t_4)) + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - t_5))))); 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[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[t$95$1], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(1.0 - N[(t$95$0 * N[(0.5 - N[(N[Cos[N[(2.0 * t$95$1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi1, -0.035], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$5], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 0.0066], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$4 * t$95$4), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$5), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := 0.5 \cdot \left(\lambda_1 - \lambda_2\right)\\
t_2 := {\sin t\_1}^{2}\\
t_3 := \sqrt{1 - \mathsf{fma}\left(t\_0, 0.5 - \frac{\cos \left(2 \cdot t\_1\right)}{2}, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_5 := \cos \phi_1 \cdot t\_2 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -0.035:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{t\_5}}{t\_3}\\
\mathbf{elif}\;\phi_1 \leq 0.0066:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{t\_3}\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_4 \cdot t\_4\right) + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{1 - t\_5}}\right)\\
\end{array}
\end{array}
if phi1 < -0.035000000000000003Initial program 50.9%
associate-*r*50.9%
*-commutative50.9%
Simplified51.0%
sin-mult51.0%
div-inv51.0%
metadata-eval51.0%
div-inv51.0%
metadata-eval51.0%
cos-sum51.0%
cos-251.0%
div-inv51.0%
metadata-eval51.0%
Applied egg-rr51.0%
div-sub51.0%
+-inverses51.0%
+-inverses51.0%
+-inverses51.0%
cos-051.0%
metadata-eval51.0%
*-commutative51.0%
Simplified51.0%
Taylor expanded in phi2 around 0 51.6%
if -0.035000000000000003 < phi1 < 0.0066Initial program 77.6%
associate-*r*77.6%
*-commutative77.6%
Simplified77.6%
sin-mult77.6%
div-inv77.6%
metadata-eval77.6%
div-inv77.6%
metadata-eval77.6%
cos-sum77.6%
cos-277.6%
div-inv77.6%
metadata-eval77.6%
Applied egg-rr77.6%
div-sub77.6%
+-inverses77.6%
+-inverses77.6%
+-inverses77.6%
cos-077.6%
metadata-eval77.6%
*-commutative77.6%
Simplified77.6%
Taylor expanded in phi1 around 0 75.7%
if 0.0066 < phi1 Initial program 43.1%
associate-*l*43.1%
Simplified43.1%
Taylor expanded in phi2 around 0 44.9%
Taylor expanded in phi1 around inf 45.0%
Final simplification62.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (sin (* 0.5 (- phi1 phi2)))))
(if (or (<= phi1 -7e-17) (not (<= phi1 4.2e-92)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_1 t_1))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt
(-
1.0
(+
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* 0.5 phi1)) 2.0)))))))
(*
(* R 2.0)
(atan2
(hypot (sqrt (* (cos phi1) t_0)) t_2)
(sqrt (- 1.0 (fma (cos phi1) t_0 (pow t_2 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sin((0.5 * (phi1 - phi2)));
double tmp;
if ((phi1 <= -7e-17) || !(phi1 <= 4.2e-92)) {
tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_1 * t_1)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - ((cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + pow(sin((0.5 * phi1)), 2.0))))));
} else {
tmp = (R * 2.0) * atan2(hypot(sqrt((cos(phi1) * t_0)), t_2), sqrt((1.0 - fma(cos(phi1), t_0, pow(t_2, 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(0.5 * Float64(phi1 - phi2))) tmp = 0.0 if ((phi1 <= -7e-17) || !(phi1 <= 4.2e-92)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sqrt(Float64(cos(phi1) * t_0)), t_2), sqrt(Float64(1.0 - fma(cos(phi1), t_0, (t_2 ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -7e-17], N[Not[LessEqual[phi1, 4.2e-92]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]], $MachinePrecision] ^ 2 + t$95$2 ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$0 + N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\\
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)\\
\mathbf{if}\;\phi_1 \leq -7 \cdot 10^{-17} \lor \neg \left(\phi_1 \leq 4.2 \cdot 10^{-92}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sqrt{\cos \phi_1 \cdot t\_0}, t\_2\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_0, {t\_2}^{2}\right)}}\\
\end{array}
\end{array}
if phi1 < -7.0000000000000003e-17 or 4.2e-92 < phi1 Initial program 49.2%
associate-*l*49.2%
Simplified49.2%
Taylor expanded in phi2 around 0 48.2%
unpow249.2%
sin-mult49.2%
div-inv49.2%
metadata-eval49.2%
div-inv49.2%
metadata-eval49.2%
div-inv49.2%
metadata-eval49.2%
div-inv49.2%
metadata-eval49.2%
Applied egg-rr48.2%
div-sub49.2%
+-inverses49.2%
cos-049.2%
metadata-eval49.2%
distribute-lft-out49.2%
metadata-eval49.2%
*-rgt-identity49.2%
Simplified48.2%
if -7.0000000000000003e-17 < phi1 < 4.2e-92Initial program 78.3%
associate-*r*78.3%
*-commutative78.3%
Simplified78.3%
sin-mult78.4%
div-inv78.4%
metadata-eval78.4%
div-inv78.4%
metadata-eval78.4%
cos-sum78.4%
cos-278.4%
div-inv78.4%
metadata-eval78.4%
Applied egg-rr78.4%
div-sub78.4%
+-inverses78.4%
+-inverses78.4%
+-inverses78.4%
cos-078.4%
metadata-eval78.4%
*-commutative78.4%
Simplified78.4%
Applied egg-rr64.5%
Simplified64.5%
Final simplification55.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -9.5e-9) (not (<= phi2 5e+19)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* t_0 t_1) (sin (* 0.5 lambda1)))))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))
(pow (sin (* 0.5 phi2)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* t_1 t_1)) (- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt
(-
1.0
(+
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* 0.5 phi1)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -9.5e-9) || !(phi2 <= 5e+19)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_0 * t_1) * sin((0.5 * lambda1))))), sqrt((1.0 - ((cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0)) + pow(sin((0.5 * phi2)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_1)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - ((cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + pow(sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
if ((phi2 <= (-9.5d-9)) .or. (.not. (phi2 <= 5d+19))) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((t_0 * t_1) * sin((0.5d0 * lambda1))))), sqrt((1.0d0 - ((cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0)) + (sin((0.5d0 * phi2)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * (t_1 * t_1)) + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt((1.0d0 - ((cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (sin((0.5d0 * phi1)) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -9.5e-9) || !(phi2 <= 5e+19)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_0 * t_1) * Math.sin((0.5 * lambda1))))), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0)) + Math.pow(Math.sin((0.5 * phi2)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_1 * t_1)) + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((1.0 - ((Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + Math.pow(Math.sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (phi2 <= -9.5e-9) or not (phi2 <= 5e+19): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_0 * t_1) * math.sin((0.5 * lambda1))))), math.sqrt((1.0 - ((math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0)) + math.pow(math.sin((0.5 * phi2)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * (t_1 * t_1)) + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt((1.0 - ((math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + math.pow(math.sin((0.5 * phi1)), 2.0)))))) 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)) tmp = 0.0 if ((phi2 <= -9.5e-9) || !(phi2 <= 5e+19)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_0 * t_1) * sin(Float64(0.5 * lambda1))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0)) + (sin(Float64(0.5 * phi2)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_1 * t_1)) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((phi2 <= -9.5e-9) || ~((phi2 <= 5e+19))) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((t_0 * t_1) * sin((0.5 * lambda1))))), sqrt((1.0 - ((cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0)) + (sin((0.5 * phi2)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_1)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - ((cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + (sin((0.5 * phi1)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -9.5e-9], N[Not[LessEqual[phi2, 5e+19]], $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[(t$95$0 * t$95$1), $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -9.5 \cdot 10^{-9} \lor \neg \left(\phi_2 \leq 5 \cdot 10^{+19}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_0 \cdot t\_1\right) \cdot \sin \left(0.5 \cdot \lambda_1\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2} + {\sin \left(0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_1 \cdot t\_1\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -9.5000000000000007e-9 or 5e19 < phi2 Initial program 51.2%
div-sub51.2%
sin-diff53.2%
Applied egg-rr53.2%
Taylor expanded in lambda1 around 0 42.1%
Taylor expanded in lambda2 around 0 32.4%
Taylor expanded in phi1 around 0 31.4%
if -9.5000000000000007e-9 < phi2 < 5e19Initial program 74.4%
associate-*l*74.4%
Simplified74.5%
Taylor expanded in phi2 around 0 73.9%
unpow274.5%
sin-mult74.5%
div-inv74.5%
metadata-eval74.5%
div-inv74.5%
metadata-eval74.5%
div-inv74.5%
metadata-eval74.5%
div-inv74.5%
metadata-eval74.5%
Applied egg-rr70.2%
div-sub74.5%
+-inverses74.5%
cos-074.5%
metadata-eval74.5%
distribute-lft-out74.5%
metadata-eval74.5%
*-rgt-identity74.5%
Simplified70.2%
Final simplification50.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- phi1 phi2))) 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) (- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))
t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
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) * ((0.5 * cos((lambda1 - lambda2))) - 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 = sin((0.5d0 * (phi1 - phi2))) ** 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) * ((0.5d0 * cos((lambda1 - lambda2))) - 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.sin((0.5 * (phi1 - phi2))), 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) * ((0.5 * Math.cos((lambda1 - lambda2))) - 0.5))) - t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (phi1 - phi2))), 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) * ((0.5 * math.cos((lambda1 - lambda2))) - 0.5))) - t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 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(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))) - t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))) ^ 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) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) - t_0))))); 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]}, 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[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{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(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)\right) - t\_0\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*r*62.4%
*-commutative62.4%
Simplified62.4%
sin-mult62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
cos-sum62.4%
cos-262.4%
div-inv62.4%
metadata-eval62.4%
Applied egg-rr62.4%
div-sub62.4%
+-inverses62.4%
+-inverses62.4%
+-inverses62.4%
cos-062.4%
metadata-eval62.4%
*-commutative62.4%
Simplified62.4%
Taylor expanded in phi1 around 0 62.4%
Final simplification62.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt
(-
1.0
(+
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* 0.5 phi1)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - ((cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + pow(sin((0.5 * phi1)), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt((1.0d0 - ((cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (sin((0.5d0 * phi1)) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((1.0 - ((Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + Math.pow(Math.sin((0.5 * phi1)), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt((1.0 - ((math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + math.pow(math.sin((0.5 * phi1)), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - ((cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + (sin((0.5 * phi1)) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
Taylor expanded in phi2 around 0 47.1%
unpow262.4%
sin-mult62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
Applied egg-rr45.0%
div-sub62.4%
+-inverses62.4%
cos-062.4%
metadata-eval62.4%
distribute-lft-out62.4%
metadata-eval62.4%
*-rgt-identity62.4%
Simplified45.0%
Final simplification45.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt (+ (- 2.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)) -1.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt(((2.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + -1.0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt(((2.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (-1.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)))), Math.sqrt(((2.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + -1.0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt(((2.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + -1.0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(Float64(2.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + -1.0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt(((2.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + -1.0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[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$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(2.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{\left(2 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + -1}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
Taylor expanded in phi2 around 0 47.1%
Taylor expanded in phi1 around 0 33.7%
expm1-log1p-u33.7%
*-commutative33.7%
Applied egg-rr33.7%
expm1-undefine33.8%
sub-neg33.8%
log1p-undefine33.8%
rem-exp-log33.8%
associate-+r-33.8%
metadata-eval33.8%
*-commutative33.8%
metadata-eval33.8%
Simplified33.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)
(* (cos phi1) (* (cos phi2) t_0))))
(sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
return R * (2.0 * atan2(sqrt((pow(sin((0.5 * (phi1 - phi2))), 2.0) + (cos(phi1) * (cos(phi2) * t_0)))), sqrt((1.0 - t_0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((sin((0.5d0 * (phi1 - phi2))) ** 2.0d0) + (cos(phi1) * (cos(phi2) * t_0)))), sqrt((1.0d0 - t_0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0) + (Math.cos(phi1) * (Math.cos(phi2) * t_0)))), Math.sqrt((1.0 - t_0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0) + (math.cos(phi1) * (math.cos(phi2) * t_0)))), math.sqrt((1.0 - t_0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * t_0)))), sqrt(Float64(1.0 - t_0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((sin((0.5 * (phi1 - phi2))) ^ 2.0) + (cos(phi1) * (cos(phi2) * t_0)))), sqrt((1.0 - t_0)))); 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]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[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] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot t\_0\right)}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
Taylor expanded in phi2 around 0 47.1%
Taylor expanded in phi1 around 0 33.7%
Taylor expanded in phi1 around 0 33.7%
Final simplification33.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt (+ (- 2.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)) -1.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt(((2.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + -1.0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt(((2.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (-1.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt(((2.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + -1.0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt(((2.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + -1.0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(Float64(2.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + -1.0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt(((2.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + -1.0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(2.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{\left(2 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + -1}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
Taylor expanded in phi2 around 0 47.1%
Taylor expanded in phi1 around 0 33.7%
unpow262.4%
sin-mult62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
Applied egg-rr31.6%
div-sub62.4%
+-inverses62.4%
cos-062.4%
metadata-eval62.4%
distribute-lft-out62.4%
metadata-eval62.4%
*-rgt-identity62.4%
Simplified31.6%
expm1-log1p-u33.7%
*-commutative33.7%
Applied egg-rr31.6%
expm1-undefine33.8%
sub-neg33.8%
log1p-undefine33.8%
rem-exp-log33.8%
associate-+r-33.8%
metadata-eval33.8%
*-commutative33.8%
metadata-eval33.8%
Simplified31.7%
Final simplification31.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
Taylor expanded in phi2 around 0 47.1%
Taylor expanded in phi1 around 0 33.7%
unpow262.4%
sin-mult62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
Applied egg-rr31.6%
div-sub62.4%
+-inverses62.4%
cos-062.4%
metadata-eval62.4%
distribute-lft-out62.4%
metadata-eval62.4%
*-rgt-identity62.4%
Simplified31.6%
Final simplification31.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (- lambda1 lambda2))))
(*
2.0
(*
R
(atan2
(sqrt
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 t_0)))
(+ 0.5 (* -0.5 (cos (- phi1 phi2))))))
(sqrt (+ 0.5 (* 0.5 t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((lambda1 - lambda2));
return 2.0 * (R * atan2(sqrt(fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * t_0))), (0.5 + (-0.5 * cos((phi1 - phi2)))))), sqrt((0.5 + (0.5 * t_0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(lambda1 - lambda2)) return Float64(2.0 * Float64(R * atan(sqrt(fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * t_0))), Float64(0.5 + Float64(-0.5 * cos(Float64(phi1 - phi2)))))), sqrt(Float64(0.5 + Float64(0.5 * t_0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]}, N[(2.0 * N[(R * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.5 + N[(-0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(0.5 + N[(0.5 * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\lambda_1 - \lambda_2\right)\\
2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot t\_0\right), 0.5 + -0.5 \cdot \cos \left(\phi_1 - \phi_2\right)\right)}}{\sqrt{0.5 + 0.5 \cdot t\_0}}\right)
\end{array}
\end{array}
Initial program 62.4%
associate-*l*62.4%
Simplified62.4%
Taylor expanded in phi2 around 0 47.1%
Taylor expanded in phi1 around 0 33.7%
unpow262.4%
sin-mult62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
div-inv62.4%
metadata-eval62.4%
Applied egg-rr31.6%
div-sub62.4%
+-inverses62.4%
cos-062.4%
metadata-eval62.4%
distribute-lft-out62.4%
metadata-eval62.4%
*-rgt-identity62.4%
Simplified31.6%
Applied egg-rr29.6%
unpow129.6%
associate-*l*29.6%
Simplified29.6%
Final simplification29.6%
herbie shell --seed 2024135
(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))))))))))