
(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 23 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 phi1)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma (cos (* phi2 -0.5)) t_0 (* t_1 (sin (* phi2 -0.5)))) 2.0)
(* t_2 (* t_3 t_3))))
(sqrt
(+
(-
1.0
(pow (- (* t_0 (cos (* phi2 0.5))) (* t_1 (sin (* phi2 0.5)))) 2.0))
(* t_2 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * phi1));
double t_1 = cos((0.5 * phi1));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(cos((phi2 * -0.5)), t_0, (t_1 * sin((phi2 * -0.5)))), 2.0) + (t_2 * (t_3 * t_3)))), sqrt(((1.0 - pow(((t_0 * cos((phi2 * 0.5))) - (t_1 * sin((phi2 * 0.5)))), 2.0)) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi1)) t_1 = cos(Float64(0.5 * phi1)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(cos(Float64(phi2 * -0.5)), t_0, Float64(t_1 * sin(Float64(phi2 * -0.5)))) ^ 2.0) + Float64(t_2 * Float64(t_3 * t_3)))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_0 * cos(Float64(phi2 * 0.5))) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0)) + Float64(t_2 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0 + N[(t$95$1 * N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \phi_1\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(\phi_2 \cdot -0.5\right), t\_0, t\_1 \cdot \sin \left(\phi_2 \cdot -0.5\right)\right)\right)}^{2} + t\_2 \cdot \left(t\_3 \cdot t\_3\right)}}{\sqrt{\left(1 - {\left(t\_0 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) + t\_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
Applied egg-rr63.6%
div-sub62.6%
sin-diff63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
Applied egg-rr80.6%
Taylor expanded in phi1 around inf 80.6%
fma-neg80.6%
cos-neg80.6%
distribute-lft-neg-in80.6%
metadata-eval80.6%
*-commutative80.6%
distribute-rgt-neg-in80.6%
sin-neg80.6%
distribute-lft-neg-in80.6%
metadata-eval80.6%
*-commutative80.6%
Simplified80.6%
sin-mult80.6%
cos-sum80.6%
cos-280.6%
div-sub80.6%
+-inverses80.6%
Applied egg-rr80.6%
cos-080.6%
metadata-eval80.6%
Simplified80.6%
Final simplification80.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(pow
(-
(* (sin (* 0.5 phi1)) (cos (* phi2 0.5)))
(* (cos (* 0.5 phi1)) (sin (* phi2 0.5))))
2.0))
(t_2 (sqrt (+ (* (* (cos phi1) (cos phi2)) (* t_0 t_0)) t_1))))
(if (or (<= lambda2 -1.4e-5) (not (<= lambda2 7.5e-5)))
(*
R
(*
2.0
(atan2
t_2
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0)))
t_1))))))
(*
R
(*
2.0
(atan2
t_2
(sqrt
(-
1.0
(+
t_1
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 lambda1)) 2.0))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(((sin((0.5 * phi1)) * cos((phi2 * 0.5))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))), 2.0);
double t_2 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + t_1));
double tmp;
if ((lambda2 <= -1.4e-5) || !(lambda2 <= 7.5e-5)) {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0))) + t_1)))));
} else {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - (t_1 + (cos(phi1) * (cos(phi2) * pow(sin((0.5 * lambda1)), 2.0))))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = ((sin((0.5d0 * phi1)) * cos((phi2 * 0.5d0))) - (cos((0.5d0 * phi1)) * sin((phi2 * 0.5d0)))) ** 2.0d0
t_2 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + t_1))
if ((lambda2 <= (-1.4d-5)) .or. (.not. (lambda2 <= 7.5d-5))) then
tmp = r * (2.0d0 * atan2(t_2, sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 2.0d0))) + t_1)))))
else
tmp = r * (2.0d0 * atan2(t_2, sqrt((1.0d0 - (t_1 + (cos(phi1) * (cos(phi2) * (sin((0.5d0 * lambda1)) ** 2.0d0))))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(((Math.sin((0.5 * phi1)) * Math.cos((phi2 * 0.5))) - (Math.cos((0.5 * phi1)) * Math.sin((phi2 * 0.5)))), 2.0);
double t_2 = Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + t_1));
double tmp;
if ((lambda2 <= -1.4e-5) || !(lambda2 <= 7.5e-5)) {
tmp = R * (2.0 * Math.atan2(t_2, Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0))) + t_1)))));
} else {
tmp = R * (2.0 * Math.atan2(t_2, Math.sqrt((1.0 - (t_1 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * lambda1)), 2.0))))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(((math.sin((0.5 * phi1)) * math.cos((phi2 * 0.5))) - (math.cos((0.5 * phi1)) * math.sin((phi2 * 0.5)))), 2.0) t_2 = math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + t_1)) tmp = 0 if (lambda2 <= -1.4e-5) or not (lambda2 <= 7.5e-5): tmp = R * (2.0 * math.atan2(t_2, math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0))) + t_1))))) else: tmp = R * (2.0 * math.atan2(t_2, math.sqrt((1.0 - (t_1 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * lambda1)), 2.0)))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(sin(Float64(0.5 * phi1)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_2 = sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + t_1)) tmp = 0.0 if ((lambda2 <= -1.4e-5) || !(lambda2 <= 7.5e-5)) tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0))) + t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - Float64(t_1 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * lambda1)) ^ 2.0))))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = ((sin((0.5 * phi1)) * cos((phi2 * 0.5))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))) ^ 2.0; t_2 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + t_1)); tmp = 0.0; if ((lambda2 <= -1.4e-5) || ~((lambda2 <= 7.5e-5))) tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0))) + t_1))))); else tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - (t_1 + (cos(phi1) * (cos(phi2) * (sin((0.5 * lambda1)) ^ 2.0)))))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[(N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda2, -1.4e-5], N[Not[LessEqual[lambda2, 7.5e-5]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(t$95$1 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\left(\sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_2 := \sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + t\_1}\\
\mathbf{if}\;\lambda_2 \leq -1.4 \cdot 10^{-5} \lor \neg \left(\lambda_2 \leq 7.5 \cdot 10^{-5}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}\right) + t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{1 - \left(t\_1 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right)\right)}}\right)\\
\end{array}
\end{array}
if lambda2 < -1.39999999999999998e-5 or 7.49999999999999934e-5 < lambda2 Initial program 49.3%
associate-*l*49.3%
Simplified49.3%
div-sub49.3%
sin-diff50.2%
div-inv50.2%
metadata-eval50.2%
div-inv50.2%
metadata-eval50.2%
div-inv50.2%
metadata-eval50.2%
div-inv50.2%
metadata-eval50.2%
Applied egg-rr50.2%
div-sub49.3%
sin-diff50.2%
div-inv50.2%
metadata-eval50.2%
div-inv50.2%
metadata-eval50.2%
div-inv50.2%
metadata-eval50.2%
div-inv50.2%
metadata-eval50.2%
Applied egg-rr60.0%
Taylor expanded in lambda1 around 0 59.8%
if -1.39999999999999998e-5 < lambda2 < 7.49999999999999934e-5Initial program 73.8%
associate-*l*73.8%
Simplified73.9%
div-sub73.9%
sin-diff75.0%
div-inv75.0%
metadata-eval75.0%
div-inv75.0%
metadata-eval75.0%
div-inv75.0%
metadata-eval75.0%
div-inv75.0%
metadata-eval75.0%
Applied egg-rr75.0%
div-sub73.9%
sin-diff75.0%
div-inv75.0%
metadata-eval75.0%
div-inv75.0%
metadata-eval75.0%
div-inv75.0%
metadata-eval75.0%
div-inv75.0%
metadata-eval75.0%
Applied egg-rr98.2%
Taylor expanded in lambda2 around 0 98.2%
Final simplification80.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (sin (* 0.5 phi1)) (cos (* phi2 0.5)))
(* (cos (* 0.5 phi1)) (sin (* phi2 0.5))))
2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (cos phi1) (cos phi2)) (* t_1 t_1))))
(if (or (<= lambda1 -6.5e-6) (not (<= lambda1 6.5e-6)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (- 1.0 t_0) t_2)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 t_0))
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0)))
t_0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((sin((0.5 * phi1)) * cos((phi2 * 0.5))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1);
double tmp;
if ((lambda1 <= -6.5e-6) || !(lambda1 <= 6.5e-6)) {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - t_0) - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_2 + t_0)), sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0))) + t_0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = ((sin((0.5d0 * phi1)) * cos((phi2 * 0.5d0))) - (cos((0.5d0 * phi1)) * sin((phi2 * 0.5d0)))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1)
if ((lambda1 <= (-6.5d-6)) .or. (.not. (lambda1 <= 6.5d-6))) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - t_0) - t_2))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_2 + t_0)), sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 2.0d0))) + t_0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.sin((0.5 * phi1)) * Math.cos((phi2 * 0.5))) - (Math.cos((0.5 * phi1)) * Math.sin((phi2 * 0.5)))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = (Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1);
double tmp;
if ((lambda1 <= -6.5e-6) || !(lambda1 <= 6.5e-6)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - t_0) - t_2))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + t_0)), Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0))) + t_0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.sin((0.5 * phi1)) * math.cos((phi2 * 0.5))) - (math.cos((0.5 * phi1)) * math.sin((phi2 * 0.5)))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = (math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1) tmp = 0 if (lambda1 <= -6.5e-6) or not (lambda1 <= 6.5e-6): tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - t_0) - t_2)))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + t_0)), math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0))) + t_0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(sin(Float64(0.5 * phi1)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) tmp = 0.0 if ((lambda1 <= -6.5e-6) || !(lambda1 <= 6.5e-6)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - t_0) - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + t_0)), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0))) + t_0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((sin((0.5 * phi1)) * cos((phi2 * 0.5))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1); tmp = 0.0; if ((lambda1 <= -6.5e-6) || ~((lambda1 <= 6.5e-6))) tmp = R * (2.0 * atan2(sqrt((t_2 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - t_0) - t_2)))); else tmp = R * (2.0 * atan2(sqrt((t_2 + t_0)), sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0))) + t_0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[lambda1, -6.5e-6], N[Not[LessEqual[lambda1, 6.5e-6]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$0), $MachinePrecision] - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)\\
\mathbf{if}\;\lambda_1 \leq -6.5 \cdot 10^{-6} \lor \neg \left(\lambda_1 \leq 6.5 \cdot 10^{-6}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - t\_0\right) - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_0}}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}\right) + t\_0\right)}}\right)\\
\end{array}
\end{array}
if lambda1 < -6.4999999999999996e-6 or 6.4999999999999996e-6 < lambda1 Initial program 51.9%
associate-*l*51.9%
Simplified51.9%
div-sub51.9%
sin-diff53.0%
div-inv53.0%
metadata-eval53.0%
div-inv53.0%
metadata-eval53.0%
div-inv53.0%
metadata-eval53.0%
div-inv53.0%
metadata-eval53.0%
Applied egg-rr53.0%
if -6.4999999999999996e-6 < lambda1 < 6.4999999999999996e-6Initial program 76.2%
associate-*l*76.2%
Simplified76.2%
div-sub76.2%
sin-diff77.1%
div-inv77.1%
metadata-eval77.1%
div-inv77.1%
metadata-eval77.1%
div-inv77.1%
metadata-eval77.1%
div-inv77.1%
metadata-eval77.1%
Applied egg-rr77.1%
div-sub76.2%
sin-diff77.1%
div-inv77.1%
metadata-eval77.1%
div-inv77.1%
metadata-eval77.1%
div-inv77.1%
metadata-eval77.1%
div-inv77.1%
metadata-eval77.1%
Applied egg-rr99.1%
Taylor expanded in lambda1 around 0 99.1%
Final simplification73.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(-
1.0
(pow
(-
(* (sin (* 0.5 phi1)) (cos (* phi2 0.5)))
(* (cos (* 0.5 phi1)) (sin (* phi2 0.5))))
2.0))
t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(((sin((0.5 * phi1)) * cos((phi2 * 0.5))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (((sin((0.5d0 * phi1)) * cos((phi2 * 0.5d0))) - (cos((0.5d0 * phi1)) * sin((phi2 * 0.5d0)))) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - Math.pow(((Math.sin((0.5 * phi1)) * Math.cos((phi2 * 0.5))) - (Math.cos((0.5 * phi1)) * Math.sin((phi2 * 0.5)))), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - math.pow(((math.sin((0.5 * phi1)) * math.cos((phi2 * 0.5))) - (math.cos((0.5 * phi1)) * math.sin((phi2 * 0.5)))), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (Float64(Float64(sin(Float64(0.5 * phi1)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(phi2 * 0.5)))) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (((sin((0.5 * phi1)) * cos((phi2 * 0.5))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - {\left(\sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
Applied egg-rr63.6%
Final simplification63.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow
(-
(* (sin (* 0.5 phi1)) (cos (* phi2 0.5)))
(* (cos (* 0.5 phi1)) (sin (* phi2 0.5))))
2.0)))
(sqrt
(-
1.0
(+
(pow (sin (+ (* phi2 -0.5) (* 0.5 phi1))) 2.0)
(*
(cos phi2)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(((sin((0.5 * phi1)) * cos((phi2 * 0.5))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))), 2.0))), sqrt((1.0 - (pow(sin(((phi2 * -0.5) + (0.5 * phi1))), 2.0) + (cos(phi2) * (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (((sin((0.5d0 * phi1)) * cos((phi2 * 0.5d0))) - (cos((0.5d0 * phi1)) * sin((phi2 * 0.5d0)))) ** 2.0d0))), sqrt((1.0d0 - ((sin(((phi2 * (-0.5d0)) + (0.5d0 * phi1))) ** 2.0d0) + (cos(phi2) * (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(((Math.sin((0.5 * phi1)) * Math.cos((phi2 * 0.5))) - (Math.cos((0.5 * phi1)) * Math.sin((phi2 * 0.5)))), 2.0))), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi2 * -0.5) + (0.5 * phi1))), 2.0) + (Math.cos(phi2) * (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(((math.sin((0.5 * phi1)) * math.cos((phi2 * 0.5))) - (math.cos((0.5 * phi1)) * math.sin((phi2 * 0.5)))), 2.0))), math.sqrt((1.0 - (math.pow(math.sin(((phi2 * -0.5) + (0.5 * phi1))), 2.0) + (math.cos(phi2) * (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (Float64(Float64(sin(Float64(0.5 * phi1)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(phi2 * 0.5)))) ^ 2.0))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi2 * -0.5) + Float64(0.5 * phi1))) ^ 2.0) + Float64(cos(phi2) * Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (((sin((0.5 * phi1)) * cos((phi2 * 0.5))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))) ^ 2.0))), sqrt((1.0 - ((sin(((phi2 * -0.5) + (0.5 * phi1))) ^ 2.0) + (cos(phi2) * (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi2 * -0.5), $MachinePrecision] + N[(0.5 * phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $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(\sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}}}{\sqrt{1 - \left({\sin \left(\phi_2 \cdot -0.5 + 0.5 \cdot \phi_1\right)}^{2} + \cos \phi_2 \cdot \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\right)}}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
Applied egg-rr63.6%
div-sub62.6%
sin-diff63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
div-inv63.6%
metadata-eval63.6%
Applied egg-rr80.6%
sub-neg80.6%
sin-diff63.4%
*-commutative63.4%
pow263.4%
div-inv63.4%
metadata-eval63.4%
*-commutative63.4%
Applied egg-rr63.4%
unsub-neg63.4%
associate--r+63.4%
cancel-sign-sub-inv63.4%
*-commutative63.4%
metadata-eval63.4%
*-commutative63.4%
associate-*r*63.4%
*-commutative63.4%
associate-*l*63.4%
Simplified63.4%
Final simplification63.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(fabs
(+
(fma
(cos phi1)
(* (cos phi2) (fma -0.5 (cos (- lambda1 lambda2)) 0.5))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))
-1.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(fabs((fma(cos(phi1), (cos(phi2) * fma(-0.5, cos((lambda1 - lambda2)), 0.5)), pow(sin((0.5 * (phi1 - phi2))), 2.0)) + -1.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(abs(Float64(fma(cos(phi1), Float64(cos(phi2) * fma(-0.5, cos(Float64(lambda1 - lambda2)), 0.5)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) + -1.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] + 0.5), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left|\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \mathsf{fma}\left(-0.5, \cos \left(\lambda_1 - \lambda_2\right), 0.5\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) + -1\right|}}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
Applied egg-rr63.0%
unpow263.0%
rem-sqrt-square63.0%
metadata-eval63.0%
distribute-lft-neg-in63.0%
+-commutative63.0%
distribute-lft-neg-in63.0%
metadata-eval63.0%
fma-define63.0%
Simplified63.0%
Final simplification63.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (+ 1.0 (- (/ (cos (- phi1 phi2)) 2.0) 0.5)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 + ((cos((phi1 - phi2)) / 2.0d0) - 0.5d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 + ((Math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 + ((math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 + Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 + \left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right)\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
unpow262.6%
sin-mult62.6%
div-inv62.6%
metadata-eval62.6%
div-inv62.6%
metadata-eval62.6%
div-inv62.6%
metadata-eval62.6%
div-inv62.6%
metadata-eval62.6%
Applied egg-rr62.6%
div-sub62.6%
+-inverses62.6%
cos-062.6%
metadata-eval62.6%
distribute-lft-out62.6%
metadata-eval62.6%
*-rgt-identity62.6%
Simplified62.6%
Final simplification62.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (cos phi1) (cos phi2)) (* t_1 t_1)))
(t_3 (sqrt (+ t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(t_4 (sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0)))))
(if (<= phi2 -900000000000.0)
(* R (* 2.0 (atan2 (sqrt (+ t_2 (pow (sin (* phi2 -0.5)) 2.0))) t_4)))
(if (<= phi2 2700.0)
(*
R
(*
2.0
(atan2
t_3
(sqrt (- (pow (cos (* 0.5 phi1)) 2.0) (* (cos phi1) t_0))))))
(* R (* 2.0 (atan2 t_3 t_4)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1);
double t_3 = sqrt((t_2 + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_4 = sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_0)));
double tmp;
if (phi2 <= -900000000000.0) {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin((phi2 * -0.5)), 2.0))), t_4));
} else if (phi2 <= 2700.0) {
tmp = R * (2.0 * atan2(t_3, sqrt((pow(cos((0.5 * phi1)), 2.0) - (cos(phi1) * t_0)))));
} else {
tmp = R * (2.0 * atan2(t_3, t_4));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1)
t_3 = sqrt((t_2 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)))
t_4 = sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * t_0)))
if (phi2 <= (-900000000000.0d0)) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin((phi2 * (-0.5d0))) ** 2.0d0))), t_4))
else if (phi2 <= 2700.0d0) then
tmp = r * (2.0d0 * atan2(t_3, sqrt(((cos((0.5d0 * phi1)) ** 2.0d0) - (cos(phi1) * t_0)))))
else
tmp = r * (2.0d0 * atan2(t_3, t_4))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = (Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1);
double t_3 = Math.sqrt((t_2 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_4 = Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * t_0)));
double tmp;
if (phi2 <= -900000000000.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), t_4));
} else if (phi2 <= 2700.0) {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt((Math.pow(Math.cos((0.5 * phi1)), 2.0) - (Math.cos(phi1) * t_0)))));
} else {
tmp = R * (2.0 * Math.atan2(t_3, t_4));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = (math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1) t_3 = math.sqrt((t_2 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))) t_4 = math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * t_0))) tmp = 0 if phi2 <= -900000000000.0: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin((phi2 * -0.5)), 2.0))), t_4)) elif phi2 <= 2700.0: tmp = R * (2.0 * math.atan2(t_3, math.sqrt((math.pow(math.cos((0.5 * phi1)), 2.0) - (math.cos(phi1) * t_0))))) else: tmp = R * (2.0 * math.atan2(t_3, t_4)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) t_3 = sqrt(Float64(t_2 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) t_4 = sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_0))) tmp = 0.0 if (phi2 <= -900000000000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(phi2 * -0.5)) ^ 2.0))), t_4))); elseif (phi2 <= 2700.0) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - Float64(cos(phi1) * t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(t_3, t_4))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((-0.5 * (lambda2 - lambda1))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1); t_3 = sqrt((t_2 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))); t_4 = sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * t_0))); tmp = 0.0; if (phi2 <= -900000000000.0) tmp = R * (2.0 * atan2(sqrt((t_2 + (sin((phi2 * -0.5)) ^ 2.0))), t_4)); elseif (phi2 <= 2700.0) tmp = R * (2.0 * atan2(t_3, sqrt(((cos((0.5 * phi1)) ^ 2.0) - (cos(phi1) * t_0))))); else tmp = R * (2.0 * atan2(t_3, t_4)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -900000000000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2700.0], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$3 / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)\\
t_3 := \sqrt{t\_2 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
t_4 := \sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_0}\\
\mathbf{if}\;\phi_2 \leq -900000000000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{t\_4}\right)\\
\mathbf{elif}\;\phi_2 \leq 2700:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - \cos \phi_1 \cdot t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{t\_4}\right)\\
\end{array}
\end{array}
if phi2 < -9e11Initial program 50.6%
associate-*l*50.6%
Simplified50.6%
Taylor expanded in phi1 around 0 51.2%
+-commutative51.2%
associate--r+51.2%
unpow251.2%
1-sub-sin51.3%
unpow251.3%
*-commutative51.3%
unpow251.3%
unpow251.3%
Simplified51.3%
Taylor expanded in phi1 around 0 52.3%
if -9e11 < phi2 < 2700Initial program 74.9%
associate-*l*74.9%
Simplified75.0%
Taylor expanded in phi2 around 0 75.0%
Simplified75.1%
if 2700 < phi2 Initial program 48.7%
associate-*l*48.7%
Simplified48.7%
Taylor expanded in phi1 around 0 49.5%
+-commutative49.5%
associate--r+49.5%
unpow249.5%
1-sub-sin49.5%
unpow249.5%
*-commutative49.5%
unpow249.5%
unpow249.5%
Simplified49.5%
Final simplification63.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 phi1)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (cos phi1) (cos phi2)) (* t_1 t_1))))
(if (or (<= phi2 -3100000000000.0) (not (<= phi2 2700.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_2
(pow
(+
t_0
(* phi2 (+ (* -0.5 (cos (* 0.5 phi1))) (* -0.125 (* phi2 t_0)))))
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((0.5 * phi1));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1);
double tmp;
if ((phi2 <= -3100000000000.0) || !(phi2 <= 2700.0)) {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow((t_0 + (phi2 * ((-0.5 * cos((0.5 * phi1))) + (-0.125 * (phi2 * t_0))))), 2.0))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin((0.5d0 * phi1))
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1)
if ((phi2 <= (-3100000000000.0d0)) .or. (.not. (phi2 <= 2700.0d0))) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_2 + ((t_0 + (phi2 * (((-0.5d0) * cos((0.5d0 * phi1))) + ((-0.125d0) * (phi2 * t_0))))) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * phi1));
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = (Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1);
double tmp;
if ((phi2 <= -3100000000000.0) || !(phi2 <= 2700.0)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow((t_0 + (phi2 * ((-0.5 * Math.cos((0.5 * phi1))) + (-0.125 * (phi2 * t_0))))), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * phi1)) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = (math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1) tmp = 0 if (phi2 <= -3100000000000.0) or not (phi2 <= 2700.0): tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow((t_0 + (phi2 * ((-0.5 * math.cos((0.5 * phi1))) + (-0.125 * (phi2 * t_0))))), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi1)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) tmp = 0.0 if ((phi2 <= -3100000000000.0) || !(phi2 <= 2700.0)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (Float64(t_0 + Float64(phi2 * Float64(Float64(-0.5 * cos(Float64(0.5 * phi1))) + Float64(-0.125 * Float64(phi2 * t_0))))) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * phi1)); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1); tmp = 0.0; if ((phi2 <= -3100000000000.0) || ~((phi2 <= 2700.0))) tmp = R * (2.0 * atan2(sqrt((t_2 + (sin((phi2 * -0.5)) ^ 2.0))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((t_2 + ((t_0 + (phi2 * ((-0.5 * cos((0.5 * phi1))) + (-0.125 * (phi2 * t_0))))) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -3100000000000.0], N[Not[LessEqual[phi2, 2700.0]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[(t$95$0 + N[(phi2 * N[(N[(-0.5 * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(-0.125 * N[(phi2 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $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(0.5 \cdot \phi_1\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)\\
\mathbf{if}\;\phi_2 \leq -3100000000000 \lor \neg \left(\phi_2 \leq 2700\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\left(t\_0 + \phi_2 \cdot \left(-0.5 \cdot \cos \left(0.5 \cdot \phi_1\right) + -0.125 \cdot \left(\phi_2 \cdot t\_0\right)\right)\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi2 < -3.1e12 or 2700 < phi2 Initial program 49.8%
associate-*l*49.8%
Simplified49.8%
Taylor expanded in phi1 around 0 50.7%
+-commutative50.7%
associate--r+50.7%
unpow250.7%
1-sub-sin50.7%
unpow250.7%
*-commutative50.7%
unpow250.7%
unpow250.7%
Simplified50.7%
Taylor expanded in phi1 around 0 51.1%
if -3.1e12 < phi2 < 2700Initial program 74.6%
associate-*l*74.7%
Simplified74.7%
Taylor expanded in phi1 around 0 44.2%
+-commutative44.2%
associate--r+44.2%
unpow244.2%
1-sub-sin44.2%
unpow244.2%
*-commutative44.2%
unpow244.2%
unpow244.2%
Simplified44.2%
Taylor expanded in phi2 around 0 44.2%
sub-neg44.2%
mul-1-neg44.2%
unpow244.2%
1-sub-sin44.2%
distribute-lft-in44.2%
metadata-eval44.2%
associate-*r*44.2%
neg-mul-144.2%
associate-*r*44.2%
metadata-eval44.2%
distribute-lft-in44.2%
+-commutative44.2%
sub-neg44.2%
distribute-lft-in44.2%
metadata-eval44.2%
associate-*r*44.2%
neg-mul-144.2%
associate-*r*44.2%
metadata-eval44.2%
Simplified44.2%
Taylor expanded in phi2 around 0 44.3%
Final simplification47.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_2 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_2 (* t_0 t_0)) t_1))
(sqrt
(+ (- 1.0 t_1) (* t_2 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_2 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0d0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = Math.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt(((t_2 * (t_0 * t_0)) + t_1)), Math.sqrt(((1.0 - t_1) + (t_2 * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_2 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt(((t_2 * (t_0 * t_0)) + t_1)), math.sqrt(((1.0 - t_1) + (t_2 * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_2 * Float64(t_0 * t_0)) + t_1)), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_2 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_2 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$2 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 \cdot \left(t\_0 \cdot t\_0\right) + t\_1}}{\sqrt{\left(1 - t\_1\right) + t\_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
sin-mult80.6%
cos-sum80.6%
cos-280.6%
div-sub80.6%
+-inverses80.6%
Applied egg-rr62.6%
cos-080.6%
metadata-eval80.6%
Simplified62.6%
Final simplification62.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (* 0.5 phi1)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (sin (* 0.5 lambda1))))
(if (<= phi2 -7.8e+25)
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (* phi2 -0.5)) 2.0) (* t_1 (* t_3 t_4))))
t_0)))
(if (<= phi2 2700.0)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_1 (* t_3 t_3))
(pow
(+
t_2
(* phi2 (+ (* -0.5 (cos (* 0.5 phi1))) (* -0.125 (* phi2 t_2)))))
2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_1 (* t_4 t_4))))
t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin((0.5 * phi1));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = sin((0.5 * lambda1));
double tmp;
if (phi2 <= -7.8e+25) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + (t_1 * (t_3 * t_4)))), t_0));
} else if (phi2 <= 2700.0) {
tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_3 * t_3)) + pow((t_2 + (phi2 * ((-0.5 * cos((0.5 * phi1))) + (-0.125 * (phi2 * t_2))))), 2.0))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_4 * t_4)))), t_0));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))
t_1 = cos(phi1) * cos(phi2)
t_2 = sin((0.5d0 * phi1))
t_3 = sin(((lambda1 - lambda2) / 2.0d0))
t_4 = sin((0.5d0 * lambda1))
if (phi2 <= (-7.8d+25)) then
tmp = r * (2.0d0 * atan2(sqrt(((sin((phi2 * (-0.5d0))) ** 2.0d0) + (t_1 * (t_3 * t_4)))), t_0))
else if (phi2 <= 2700.0d0) then
tmp = r * (2.0d0 * atan2(sqrt(((t_1 * (t_3 * t_3)) + ((t_2 + (phi2 * (((-0.5d0) * cos((0.5d0 * phi1))) + ((-0.125d0) * (phi2 * t_2))))) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_1 * (t_4 * t_4)))), t_0))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double t_2 = Math.sin((0.5 * phi1));
double t_3 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_4 = Math.sin((0.5 * lambda1));
double tmp;
if (phi2 <= -7.8e+25) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi2 * -0.5)), 2.0) + (t_1 * (t_3 * t_4)))), t_0));
} else if (phi2 <= 2700.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_1 * (t_3 * t_3)) + Math.pow((t_2 + (phi2 * ((-0.5 * Math.cos((0.5 * phi1))) + (-0.125 * (phi2 * t_2))))), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_4 * t_4)))), t_0));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))) t_1 = math.cos(phi1) * math.cos(phi2) t_2 = math.sin((0.5 * phi1)) t_3 = math.sin(((lambda1 - lambda2) / 2.0)) t_4 = math.sin((0.5 * lambda1)) tmp = 0 if phi2 <= -7.8e+25: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi2 * -0.5)), 2.0) + (t_1 * (t_3 * t_4)))), t_0)) elif phi2 <= 2700.0: tmp = R * (2.0 * math.atan2(math.sqrt(((t_1 * (t_3 * t_3)) + math.pow((t_2 + (phi2 * ((-0.5 * math.cos((0.5 * phi1))) + (-0.125 * (phi2 * t_2))))), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_4 * t_4)))), t_0)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(0.5 * phi1)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = sin(Float64(0.5 * lambda1)) tmp = 0.0 if (phi2 <= -7.8e+25) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + Float64(t_1 * Float64(t_3 * t_4)))), t_0))); elseif (phi2 <= 2700.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_3 * t_3)) + (Float64(t_2 + Float64(phi2 * Float64(Float64(-0.5 * cos(Float64(0.5 * phi1))) + Float64(-0.125 * Float64(phi2 * t_2))))) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(t_4 * t_4)))), t_0))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))); t_1 = cos(phi1) * cos(phi2); t_2 = sin((0.5 * phi1)); t_3 = sin(((lambda1 - lambda2) / 2.0)); t_4 = sin((0.5 * lambda1)); tmp = 0.0; if (phi2 <= -7.8e+25) tmp = R * (2.0 * atan2(sqrt(((sin((phi2 * -0.5)) ^ 2.0) + (t_1 * (t_3 * t_4)))), t_0)); elseif (phi2 <= 2700.0) tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_3 * t_3)) + ((t_2 + (phi2 * ((-0.5 * cos((0.5 * phi1))) + (-0.125 * (phi2 * t_2))))) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); else tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_1 * (t_4 * t_4)))), t_0)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -7.8e+25], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(t$95$3 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2700.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$2 + N[(phi2 * N[(N[(-0.5 * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(-0.125 * N[(phi2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $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], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(t$95$4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(0.5 \cdot \phi_1\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \sin \left(0.5 \cdot \lambda_1\right)\\
\mathbf{if}\;\phi_2 \leq -7.8 \cdot 10^{+25}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + t\_1 \cdot \left(t\_3 \cdot t\_4\right)}}{t\_0}\right)\\
\mathbf{elif}\;\phi_2 \leq 2700:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_3 \cdot t\_3\right) + {\left(t\_2 + \phi_2 \cdot \left(-0.5 \cdot \cos \left(0.5 \cdot \phi_1\right) + -0.125 \cdot \left(\phi_2 \cdot t\_2\right)\right)\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \left(t\_4 \cdot t\_4\right)}}{t\_0}\right)\\
\end{array}
\end{array}
if phi2 < -7.8000000000000004e25Initial program 51.3%
associate-*l*51.3%
Simplified51.3%
Taylor expanded in phi1 around 0 52.3%
+-commutative52.3%
associate--r+52.3%
unpow252.3%
1-sub-sin52.4%
unpow252.4%
*-commutative52.4%
unpow252.4%
unpow252.4%
Simplified52.4%
Taylor expanded in lambda2 around 0 41.1%
Taylor expanded in phi1 around 0 41.8%
if -7.8000000000000004e25 < phi2 < 2700Initial program 74.0%
associate-*l*74.0%
Simplified74.1%
Taylor expanded in phi1 around 0 44.0%
+-commutative44.0%
associate--r+44.0%
unpow244.0%
1-sub-sin44.0%
unpow244.0%
*-commutative44.0%
unpow244.0%
unpow244.0%
Simplified44.0%
Taylor expanded in phi2 around 0 43.8%
sub-neg43.8%
mul-1-neg43.8%
unpow243.8%
1-sub-sin43.8%
distribute-lft-in43.8%
metadata-eval43.8%
associate-*r*43.8%
neg-mul-143.8%
associate-*r*43.8%
metadata-eval43.8%
distribute-lft-in43.8%
+-commutative43.8%
sub-neg43.8%
distribute-lft-in43.8%
metadata-eval43.8%
associate-*r*43.8%
neg-mul-143.8%
associate-*r*43.8%
metadata-eval43.8%
Simplified43.8%
Taylor expanded in phi2 around 0 44.0%
if 2700 < phi2 Initial program 48.7%
associate-*l*48.7%
Simplified48.7%
Taylor expanded in phi1 around 0 49.5%
+-commutative49.5%
associate--r+49.5%
unpow249.5%
1-sub-sin49.5%
unpow249.5%
*-commutative49.5%
unpow249.5%
unpow249.5%
Simplified49.5%
Taylor expanded in lambda2 around 0 43.5%
Taylor expanded in lambda2 around 0 43.9%
Final simplification43.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* 0.5 phi1)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_0 (* t_2 (sin (* 0.5 lambda1)))))
(t_4 (pow (cos (* phi2 -0.5)) 2.0)))
(if (<= phi2 -7.8e+25)
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (* phi2 -0.5)) 2.0) t_3))
(sqrt
(-
t_4
(* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
(if (<= phi2 2700.0)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* t_2 t_2))
(pow
(+
t_1
(* phi2 (+ (* -0.5 (cos (* 0.5 phi1))) (* -0.125 (* phi2 t_1)))))
2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_3))
(sqrt
(+
t_4
(* (cos phi2) (/ (+ (cos (- lambda2 lambda1)) -1.0) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((0.5 * phi1));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_0 * (t_2 * sin((0.5 * lambda1)));
double t_4 = pow(cos((phi2 * -0.5)), 2.0);
double tmp;
if (phi2 <= -7.8e+25) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + t_3)), sqrt((t_4 - (cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else if (phi2 <= 2700.0) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_2 * t_2)) + pow((t_1 + (phi2 * ((-0.5 * cos((0.5 * phi1))) + (-0.125 * (phi2 * t_1))))), 2.0))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_3)), sqrt((t_4 + (cos(phi2) * ((cos((lambda2 - lambda1)) + -1.0) / 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) :: tmp
t_0 = cos(phi1) * cos(phi2)
t_1 = sin((0.5d0 * phi1))
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = t_0 * (t_2 * sin((0.5d0 * lambda1)))
t_4 = cos((phi2 * (-0.5d0))) ** 2.0d0
if (phi2 <= (-7.8d+25)) then
tmp = r * (2.0d0 * atan2(sqrt(((sin((phi2 * (-0.5d0))) ** 2.0d0) + t_3)), sqrt((t_4 - (cos(phi2) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
else if (phi2 <= 2700.0d0) then
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * (t_2 * t_2)) + ((t_1 + (phi2 * (((-0.5d0) * cos((0.5d0 * phi1))) + ((-0.125d0) * (phi2 * t_1))))) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_3)), sqrt((t_4 + (cos(phi2) * ((cos((lambda2 - lambda1)) + (-1.0d0)) / 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.sin((0.5 * phi1));
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_0 * (t_2 * Math.sin((0.5 * lambda1)));
double t_4 = Math.pow(Math.cos((phi2 * -0.5)), 2.0);
double tmp;
if (phi2 <= -7.8e+25) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi2 * -0.5)), 2.0) + t_3)), Math.sqrt((t_4 - (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else if (phi2 <= 2700.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_2 * t_2)) + Math.pow((t_1 + (phi2 * ((-0.5 * Math.cos((0.5 * phi1))) + (-0.125 * (phi2 * t_1))))), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_3)), Math.sqrt((t_4 + (Math.cos(phi2) * ((Math.cos((lambda2 - lambda1)) + -1.0) / 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin((0.5 * phi1)) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = t_0 * (t_2 * math.sin((0.5 * lambda1))) t_4 = math.pow(math.cos((phi2 * -0.5)), 2.0) tmp = 0 if phi2 <= -7.8e+25: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi2 * -0.5)), 2.0) + t_3)), math.sqrt((t_4 - (math.cos(phi2) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))) elif phi2 <= 2700.0: tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * (t_2 * t_2)) + math.pow((t_1 + (phi2 * ((-0.5 * math.cos((0.5 * phi1))) + (-0.125 * (phi2 * t_1))))), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_3)), math.sqrt((t_4 + (math.cos(phi2) * ((math.cos((lambda2 - lambda1)) + -1.0) / 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * phi1)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_0 * Float64(t_2 * sin(Float64(0.5 * lambda1)))) t_4 = cos(Float64(phi2 * -0.5)) ^ 2.0 tmp = 0.0 if (phi2 <= -7.8e+25) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + t_3)), sqrt(Float64(t_4 - Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))); elseif (phi2 <= 2700.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_2 * t_2)) + (Float64(t_1 + Float64(phi2 * Float64(Float64(-0.5 * cos(Float64(0.5 * phi1))) + Float64(-0.125 * Float64(phi2 * t_1))))) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_3)), sqrt(Float64(t_4 + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) + -1.0) / 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin((0.5 * phi1)); t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = t_0 * (t_2 * sin((0.5 * lambda1))); t_4 = cos((phi2 * -0.5)) ^ 2.0; tmp = 0.0; if (phi2 <= -7.8e+25) tmp = R * (2.0 * atan2(sqrt(((sin((phi2 * -0.5)) ^ 2.0) + t_3)), sqrt((t_4 - (cos(phi2) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))))); elseif (phi2 <= 2700.0) tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_2 * t_2)) + ((t_1 + (phi2 * ((-0.5 * cos((0.5 * phi1))) + (-0.125 * (phi2 * t_1))))) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); else tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_3)), sqrt((t_4 + (cos(phi2) * ((cos((lambda2 - lambda1)) + -1.0) / 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[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$0 * N[(t$95$2 * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi2, -7.8e+25], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$4 - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2700.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$1 + N[(phi2 * N[(N[(-0.5 * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(-0.125 * N[(phi2 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $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], 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$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$4 + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] + -1.0), $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(0.5 \cdot \phi_1\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_0 \cdot \left(t\_2 \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)\\
t_4 := {\cos \left(\phi_2 \cdot -0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -7.8 \cdot 10^{+25}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + t\_3}}{\sqrt{t\_4 - \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{elif}\;\phi_2 \leq 2700:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_2 \cdot t\_2\right) + {\left(t\_1 + \phi_2 \cdot \left(-0.5 \cdot \cos \left(0.5 \cdot \phi_1\right) + -0.125 \cdot \left(\phi_2 \cdot t\_1\right)\right)\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_3}}{\sqrt{t\_4 + \cos \phi_2 \cdot \frac{\cos \left(\lambda_2 - \lambda_1\right) + -1}{2}}}\right)\\
\end{array}
\end{array}
if phi2 < -7.8000000000000004e25Initial program 51.3%
associate-*l*51.3%
Simplified51.3%
Taylor expanded in phi1 around 0 52.3%
+-commutative52.3%
associate--r+52.3%
unpow252.3%
1-sub-sin52.4%
unpow252.4%
*-commutative52.4%
unpow252.4%
unpow252.4%
Simplified52.4%
Taylor expanded in lambda2 around 0 41.1%
Taylor expanded in phi1 around 0 41.8%
if -7.8000000000000004e25 < phi2 < 2700Initial program 74.0%
associate-*l*74.0%
Simplified74.1%
Taylor expanded in phi1 around 0 44.0%
+-commutative44.0%
associate--r+44.0%
unpow244.0%
1-sub-sin44.0%
unpow244.0%
*-commutative44.0%
unpow244.0%
unpow244.0%
Simplified44.0%
Taylor expanded in phi2 around 0 43.8%
sub-neg43.8%
mul-1-neg43.8%
unpow243.8%
1-sub-sin43.8%
distribute-lft-in43.8%
metadata-eval43.8%
associate-*r*43.8%
neg-mul-143.8%
associate-*r*43.8%
metadata-eval43.8%
distribute-lft-in43.8%
+-commutative43.8%
sub-neg43.8%
distribute-lft-in43.8%
metadata-eval43.8%
associate-*r*43.8%
neg-mul-143.8%
associate-*r*43.8%
metadata-eval43.8%
Simplified43.8%
Taylor expanded in phi2 around 0 44.0%
if 2700 < phi2 Initial program 48.7%
associate-*l*48.7%
Simplified48.7%
Taylor expanded in phi1 around 0 49.5%
+-commutative49.5%
associate--r+49.5%
unpow249.5%
1-sub-sin49.5%
unpow249.5%
*-commutative49.5%
unpow249.5%
unpow249.5%
Simplified49.5%
Taylor expanded in lambda2 around 0 43.5%
unpow243.5%
sin-mult43.5%
Applied egg-rr43.5%
+-inverses43.5%
cos-043.5%
count-243.5%
associate-*r*43.5%
metadata-eval43.5%
mul-1-neg43.5%
cos-neg43.5%
Simplified43.5%
Final simplification43.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
Taylor expanded in phi1 around 0 47.3%
+-commutative47.3%
associate--r+47.3%
unpow247.3%
1-sub-sin47.4%
unpow247.4%
*-commutative47.4%
unpow247.4%
unpow247.4%
Simplified47.4%
Final simplification47.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* 0.5 phi1)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -7.8e+25) (not (<= phi2 2700.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* t_2 (sin (* 0.5 lambda1))))))
(sqrt
(+
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (/ (+ (cos (- lambda2 lambda1)) -1.0) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* t_2 t_2))
(pow
(+
t_1
(* phi2 (+ (* -0.5 (cos (* 0.5 phi1))) (* -0.125 (* phi2 t_1)))))
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 = cos(phi1) * cos(phi2);
double t_1 = sin((0.5 * phi1));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -7.8e+25) || !(phi2 <= 2700.0)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_2 * sin((0.5 * lambda1)))))), sqrt((pow(cos((phi2 * -0.5)), 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) + -1.0) / 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_2 * t_2)) + pow((t_1 + (phi2 * ((-0.5 * cos((0.5 * phi1))) + (-0.125 * (phi2 * t_1))))), 2.0))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 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 = cos(phi1) * cos(phi2)
t_1 = sin((0.5d0 * phi1))
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
if ((phi2 <= (-7.8d+25)) .or. (.not. (phi2 <= 2700.0d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_2 * sin((0.5d0 * lambda1)))))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * ((cos((lambda2 - lambda1)) + (-1.0d0)) / 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * (t_2 * t_2)) + ((t_1 + (phi2 * (((-0.5d0) * cos((0.5d0 * phi1))) + ((-0.125d0) * (phi2 * t_1))))) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 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((0.5 * phi1));
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -7.8e+25) || !(phi2 <= 2700.0)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_2 * Math.sin((0.5 * lambda1)))))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * ((Math.cos((lambda2 - lambda1)) + -1.0) / 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_2 * t_2)) + Math.pow((t_1 + (phi2 * ((-0.5 * Math.cos((0.5 * phi1))) + (-0.125 * (phi2 * t_1))))), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin((0.5 * phi1)) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (phi2 <= -7.8e+25) or not (phi2 <= 2700.0): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_2 * math.sin((0.5 * lambda1)))))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) + (math.cos(phi2) * ((math.cos((lambda2 - lambda1)) + -1.0) / 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * (t_2 * t_2)) + math.pow((t_1 + (phi2 * ((-0.5 * math.cos((0.5 * phi1))) + (-0.125 * (phi2 * t_1))))), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * phi1)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -7.8e+25) || !(phi2 <= 2700.0)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_2 * sin(Float64(0.5 * lambda1)))))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) + -1.0) / 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_2 * t_2)) + (Float64(t_1 + Float64(phi2 * Float64(Float64(-0.5 * cos(Float64(0.5 * phi1))) + Float64(-0.125 * Float64(phi2 * t_1))))) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin((0.5 * phi1)); t_2 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((phi2 <= -7.8e+25) || ~((phi2 <= 2700.0))) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_2 * sin((0.5 * lambda1)))))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) + -1.0) / 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_2 * t_2)) + ((t_1 + (phi2 * ((-0.5 * cos((0.5 * phi1))) + (-0.125 * (phi2 * t_1))))) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 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[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -7.8e+25], N[Not[LessEqual[phi2, 2700.0]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$2 * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] + -1.0), $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$2 * t$95$2), $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$1 + N[(phi2 * N[(N[(-0.5 * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(-0.125 * N[(phi2 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $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 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(0.5 \cdot \phi_1\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -7.8 \cdot 10^{+25} \lor \neg \left(\phi_2 \leq 2700\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_2 \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \frac{\cos \left(\lambda_2 - \lambda_1\right) + -1}{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_2 \cdot t\_2\right) + {\left(t\_1 + \phi_2 \cdot \left(-0.5 \cdot \cos \left(0.5 \cdot \phi_1\right) + -0.125 \cdot \left(\phi_2 \cdot t\_1\right)\right)\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi2 < -7.8000000000000004e25 or 2700 < phi2 Initial program 50.1%
associate-*l*50.1%
Simplified50.1%
Taylor expanded in phi1 around 0 51.0%
+-commutative51.0%
associate--r+51.0%
unpow251.0%
1-sub-sin51.1%
unpow251.1%
*-commutative51.1%
unpow251.1%
unpow251.1%
Simplified51.1%
Taylor expanded in lambda2 around 0 42.2%
unpow242.2%
sin-mult42.2%
Applied egg-rr42.2%
+-inverses42.2%
cos-042.2%
count-242.2%
associate-*r*42.2%
metadata-eval42.2%
mul-1-neg42.2%
cos-neg42.2%
Simplified42.2%
if -7.8000000000000004e25 < phi2 < 2700Initial program 74.0%
associate-*l*74.0%
Simplified74.1%
Taylor expanded in phi1 around 0 44.0%
+-commutative44.0%
associate--r+44.0%
unpow244.0%
1-sub-sin44.0%
unpow244.0%
*-commutative44.0%
unpow244.0%
unpow244.0%
Simplified44.0%
Taylor expanded in phi2 around 0 43.8%
sub-neg43.8%
mul-1-neg43.8%
unpow243.8%
1-sub-sin43.8%
distribute-lft-in43.8%
metadata-eval43.8%
associate-*r*43.8%
neg-mul-143.8%
associate-*r*43.8%
metadata-eval43.8%
distribute-lft-in43.8%
+-commutative43.8%
sub-neg43.8%
distribute-lft-in43.8%
metadata-eval43.8%
associate-*r*43.8%
neg-mul-143.8%
associate-*r*43.8%
metadata-eval43.8%
Simplified43.8%
Taylor expanded in phi2 around 0 44.0%
Final simplification43.1%
(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 -7.8e+25) (not (<= phi2 2700.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* t_1 (sin (* 0.5 lambda1))))))
(sqrt
(+
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (/ (+ (cos (- lambda2 lambda1)) -1.0) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* t_1 t_1))
(pow
(+ (sin (* 0.5 phi1)) (* -0.5 (* phi2 (cos (* 0.5 phi1)))))
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 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -7.8e+25) || !(phi2 <= 2700.0)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * sin((0.5 * lambda1)))))), sqrt((pow(cos((phi2 * -0.5)), 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) + -1.0) / 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_1)) + pow((sin((0.5 * phi1)) + (-0.5 * (phi2 * cos((0.5 * phi1))))), 2.0))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 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 <= (-7.8d+25)) .or. (.not. (phi2 <= 2700.0d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_1 * sin((0.5d0 * lambda1)))))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * ((cos((lambda2 - lambda1)) + (-1.0d0)) / 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * (t_1 * t_1)) + ((sin((0.5d0 * phi1)) + ((-0.5d0) * (phi2 * cos((0.5d0 * phi1))))) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 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 <= -7.8e+25) || !(phi2 <= 2700.0)) {
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((Math.pow(Math.cos((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * ((Math.cos((lambda2 - lambda1)) + -1.0) / 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_1 * t_1)) + Math.pow((Math.sin((0.5 * phi1)) + (-0.5 * (phi2 * Math.cos((0.5 * phi1))))), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 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 <= -7.8e+25) or not (phi2 <= 2700.0): 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((math.pow(math.cos((phi2 * -0.5)), 2.0) + (math.cos(phi2) * ((math.cos((lambda2 - lambda1)) + -1.0) / 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * (t_1 * t_1)) + math.pow((math.sin((0.5 * phi1)) + (-0.5 * (phi2 * math.cos((0.5 * phi1))))), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 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 <= -7.8e+25) || !(phi2 <= 2700.0)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * sin(Float64(0.5 * lambda1)))))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) + -1.0) / 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_1 * t_1)) + (Float64(sin(Float64(0.5 * phi1)) + Float64(-0.5 * Float64(phi2 * cos(Float64(0.5 * phi1))))) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 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 <= -7.8e+25) || ~((phi2 <= 2700.0))) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_1 * sin((0.5 * lambda1)))))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) + -1.0) / 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_1)) + ((sin((0.5 * phi1)) + (-0.5 * (phi2 * cos((0.5 * phi1))))) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 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, -7.8e+25], N[Not[LessEqual[phi2, 2700.0]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$1 * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] + -1.0), $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[Power[N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(-0.5 * N[(phi2 * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $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 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -7.8 \cdot 10^{+25} \lor \neg \left(\phi_2 \leq 2700\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \frac{\cos \left(\lambda_2 - \lambda_1\right) + -1}{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_1 \cdot t\_1\right) + {\left(\sin \left(0.5 \cdot \phi_1\right) + -0.5 \cdot \left(\phi_2 \cdot \cos \left(0.5 \cdot \phi_1\right)\right)\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi2 < -7.8000000000000004e25 or 2700 < phi2 Initial program 50.1%
associate-*l*50.1%
Simplified50.1%
Taylor expanded in phi1 around 0 51.0%
+-commutative51.0%
associate--r+51.0%
unpow251.0%
1-sub-sin51.1%
unpow251.1%
*-commutative51.1%
unpow251.1%
unpow251.1%
Simplified51.1%
Taylor expanded in lambda2 around 0 42.2%
unpow242.2%
sin-mult42.2%
Applied egg-rr42.2%
+-inverses42.2%
cos-042.2%
count-242.2%
associate-*r*42.2%
metadata-eval42.2%
mul-1-neg42.2%
cos-neg42.2%
Simplified42.2%
if -7.8000000000000004e25 < phi2 < 2700Initial program 74.0%
associate-*l*74.0%
Simplified74.1%
Taylor expanded in phi1 around 0 44.0%
+-commutative44.0%
associate--r+44.0%
unpow244.0%
1-sub-sin44.0%
unpow244.0%
*-commutative44.0%
unpow244.0%
unpow244.0%
Simplified44.0%
Taylor expanded in phi2 around 0 43.8%
sub-neg43.8%
mul-1-neg43.8%
unpow243.8%
1-sub-sin43.8%
distribute-lft-in43.8%
metadata-eval43.8%
associate-*r*43.8%
neg-mul-143.8%
associate-*r*43.8%
metadata-eval43.8%
distribute-lft-in43.8%
+-commutative43.8%
sub-neg43.8%
distribute-lft-in43.8%
metadata-eval43.8%
associate-*r*43.8%
neg-mul-143.8%
associate-*r*43.8%
metadata-eval43.8%
Simplified43.8%
Taylor expanded in phi2 around 0 44.0%
Final simplification43.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
(if (<= lambda1 -8.8e-39)
(* R (* 2.0 (atan2 t_1 (sqrt (pow (cos (* 0.5 lambda1)) 2.0)))))
(*
R
(* 2.0 (atan2 t_1 (sqrt (- 1.0 (pow (sin (* -0.5 lambda2)) 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 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if (lambda1 <= -8.8e-39) {
tmp = R * (2.0 * atan2(t_1, sqrt(pow(cos((0.5 * lambda1)), 2.0))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - pow(sin((-0.5 * lambda2)), 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 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)))
if (lambda1 <= (-8.8d-39)) then
tmp = r * (2.0d0 * atan2(t_1, sqrt((cos((0.5d0 * lambda1)) ** 2.0d0))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - (sin(((-0.5d0) * lambda2)) ** 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.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if (lambda1 <= -8.8e-39) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt(Math.pow(Math.cos((0.5 * lambda1)), 2.0))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * lambda2)), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))) tmp = 0 if lambda1 <= -8.8e-39: tmp = R * (2.0 * math.atan2(t_1, math.sqrt(math.pow(math.cos((0.5 * lambda1)), 2.0)))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - math.pow(math.sin((-0.5 * lambda2)), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) tmp = 0.0 if (lambda1 <= -8.8e-39) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt((cos(Float64(0.5 * lambda1)) ^ 2.0))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - (sin(Float64(-0.5 * lambda2)) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))); tmp = 0.0; if (lambda1 <= -8.8e-39) tmp = R * (2.0 * atan2(t_1, sqrt((cos((0.5 * lambda1)) ^ 2.0)))); else tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - (sin((-0.5 * lambda2)) ^ 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[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda1, -8.8e-39], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[Power[N[Cos[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
\mathbf{if}\;\lambda_1 \leq -8.8 \cdot 10^{-39}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{1 - {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}}}\right)\\
\end{array}
\end{array}
if lambda1 < -8.80000000000000003e-39Initial program 52.7%
associate-*l*52.7%
Simplified52.8%
Taylor expanded in phi1 around 0 44.0%
+-commutative44.0%
associate--r+44.0%
unpow244.0%
1-sub-sin44.1%
unpow244.1%
*-commutative44.1%
unpow244.1%
unpow244.1%
Simplified44.1%
Taylor expanded in phi2 around 0 31.8%
sub-neg31.8%
mul-1-neg31.8%
unpow231.8%
1-sub-sin31.9%
distribute-lft-in31.9%
metadata-eval31.9%
associate-*r*31.9%
neg-mul-131.9%
associate-*r*31.9%
metadata-eval31.9%
distribute-lft-in31.9%
+-commutative31.9%
sub-neg31.9%
distribute-lft-in31.9%
metadata-eval31.9%
associate-*r*31.9%
neg-mul-131.9%
associate-*r*31.9%
metadata-eval31.9%
Simplified31.8%
Taylor expanded in lambda2 around 0 31.8%
unpow231.8%
1-sub-sin31.9%
unpow231.9%
Simplified31.9%
if -8.80000000000000003e-39 < lambda1 Initial program 67.5%
associate-*l*67.5%
Simplified67.5%
Taylor expanded in phi1 around 0 49.0%
+-commutative49.0%
associate--r+49.0%
unpow249.0%
1-sub-sin49.0%
unpow249.0%
*-commutative49.0%
unpow249.0%
unpow249.0%
Simplified49.0%
Taylor expanded in phi2 around 0 33.2%
sub-neg33.2%
mul-1-neg33.2%
unpow233.2%
1-sub-sin33.2%
distribute-lft-in33.2%
metadata-eval33.2%
associate-*r*33.2%
neg-mul-133.2%
associate-*r*33.2%
metadata-eval33.2%
distribute-lft-in33.2%
+-commutative33.2%
sub-neg33.2%
distribute-lft-in33.2%
metadata-eval33.2%
associate-*r*33.2%
neg-mul-133.2%
associate-*r*33.2%
metadata-eval33.2%
Simplified33.2%
Taylor expanded in lambda1 around 0 31.4%
Final simplification31.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (+ (- 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)) + pow(sin(((phi1 - phi2) / 2.0)), 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)) + (sin(((phi1 - phi2) / 2.0d0)) ** 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)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 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)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 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)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 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)) + (sin(((phi1 - phi2) / 2.0)) ^ 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[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $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) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\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 62.5%
associate-*l*62.5%
Simplified62.6%
Taylor expanded in phi1 around 0 47.3%
+-commutative47.3%
associate--r+47.3%
unpow247.3%
1-sub-sin47.4%
unpow247.4%
*-commutative47.4%
unpow247.4%
unpow247.4%
Simplified47.4%
Taylor expanded in phi2 around 0 32.7%
sub-neg32.7%
mul-1-neg32.7%
unpow232.7%
1-sub-sin32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
distribute-lft-in32.7%
+-commutative32.7%
sub-neg32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
Simplified32.7%
expm1-log1p-u32.7%
Applied egg-rr32.7%
expm1-undefine32.7%
sub-neg32.7%
log1p-undefine32.7%
rem-exp-log32.7%
associate-+r-32.7%
metadata-eval32.7%
metadata-eval32.7%
Simplified32.7%
Final simplification32.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
(if (<= lambda1 -8.2e-39)
(* R (* 2.0 (atan2 t_1 (sqrt (pow (cos (* 0.5 lambda1)) 2.0)))))
(* R (* 2.0 (atan2 t_1 (sqrt (pow (cos (* 0.5 lambda2)) 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 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if (lambda1 <= -8.2e-39) {
tmp = R * (2.0 * atan2(t_1, sqrt(pow(cos((0.5 * lambda1)), 2.0))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt(pow(cos((0.5 * lambda2)), 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 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)))
if (lambda1 <= (-8.2d-39)) then
tmp = r * (2.0d0 * atan2(t_1, sqrt((cos((0.5d0 * lambda1)) ** 2.0d0))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt((cos((0.5d0 * lambda2)) ** 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.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if (lambda1 <= -8.2e-39) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt(Math.pow(Math.cos((0.5 * lambda1)), 2.0))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt(Math.pow(Math.cos((0.5 * lambda2)), 2.0))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))) tmp = 0 if lambda1 <= -8.2e-39: tmp = R * (2.0 * math.atan2(t_1, math.sqrt(math.pow(math.cos((0.5 * lambda1)), 2.0)))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt(math.pow(math.cos((0.5 * lambda2)), 2.0)))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) tmp = 0.0 if (lambda1 <= -8.2e-39) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt((cos(Float64(0.5 * lambda1)) ^ 2.0))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt((cos(Float64(0.5 * lambda2)) ^ 2.0))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))); tmp = 0.0; if (lambda1 <= -8.2e-39) tmp = R * (2.0 * atan2(t_1, sqrt((cos((0.5 * lambda1)) ^ 2.0)))); else tmp = R * (2.0 * atan2(t_1, sqrt((cos((0.5 * lambda2)) ^ 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[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda1, -8.2e-39], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[Power[N[Cos[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[Power[N[Cos[N[(0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
\mathbf{if}\;\lambda_1 \leq -8.2 \cdot 10^{-39}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(0.5 \cdot \lambda_2\right)}^{2}}}\right)\\
\end{array}
\end{array}
if lambda1 < -8.2e-39Initial program 52.7%
associate-*l*52.7%
Simplified52.8%
Taylor expanded in phi1 around 0 44.0%
+-commutative44.0%
associate--r+44.0%
unpow244.0%
1-sub-sin44.1%
unpow244.1%
*-commutative44.1%
unpow244.1%
unpow244.1%
Simplified44.1%
Taylor expanded in phi2 around 0 31.8%
sub-neg31.8%
mul-1-neg31.8%
unpow231.8%
1-sub-sin31.9%
distribute-lft-in31.9%
metadata-eval31.9%
associate-*r*31.9%
neg-mul-131.9%
associate-*r*31.9%
metadata-eval31.9%
distribute-lft-in31.9%
+-commutative31.9%
sub-neg31.9%
distribute-lft-in31.9%
metadata-eval31.9%
associate-*r*31.9%
neg-mul-131.9%
associate-*r*31.9%
metadata-eval31.9%
Simplified31.8%
Taylor expanded in lambda2 around 0 31.8%
unpow231.8%
1-sub-sin31.9%
unpow231.9%
Simplified31.9%
if -8.2e-39 < lambda1 Initial program 67.5%
associate-*l*67.5%
Simplified67.5%
Taylor expanded in phi1 around 0 49.0%
+-commutative49.0%
associate--r+49.0%
unpow249.0%
1-sub-sin49.0%
unpow249.0%
*-commutative49.0%
unpow249.0%
unpow249.0%
Simplified49.0%
Taylor expanded in phi2 around 0 33.2%
sub-neg33.2%
mul-1-neg33.2%
unpow233.2%
1-sub-sin33.2%
distribute-lft-in33.2%
metadata-eval33.2%
associate-*r*33.2%
neg-mul-133.2%
associate-*r*33.2%
metadata-eval33.2%
distribute-lft-in33.2%
+-commutative33.2%
sub-neg33.2%
distribute-lft-in33.2%
metadata-eval33.2%
associate-*r*33.2%
neg-mul-133.2%
associate-*r*33.2%
metadata-eval33.2%
Simplified33.2%
Taylor expanded in lambda1 around 0 31.4%
unpow231.4%
1-sub-sin31.4%
unpow231.4%
*-commutative31.4%
metadata-eval31.4%
distribute-rgt-neg-in31.4%
cos-neg31.4%
Simplified31.4%
Final simplification31.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[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) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
Taylor expanded in phi1 around 0 47.3%
+-commutative47.3%
associate--r+47.3%
unpow247.3%
1-sub-sin47.4%
unpow247.4%
*-commutative47.4%
unpow247.4%
unpow247.4%
Simplified47.4%
Taylor expanded in phi2 around 0 32.7%
sub-neg32.7%
mul-1-neg32.7%
unpow232.7%
1-sub-sin32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
distribute-lft-in32.7%
+-commutative32.7%
sub-neg32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
Simplified32.7%
Final simplification32.7%
(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))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (pow (cos (* 0.5 lambda1)) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(pow(cos((0.5 * lambda1)), 2.0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((cos((0.5d0 * lambda1)) ** 2.0d0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(Math.pow(Math.cos((0.5 * lambda1)), 2.0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(math.pow(math.cos((0.5 * lambda1)), 2.0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((cos(Float64(0.5 * lambda1)) ^ 2.0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((cos((0.5 * lambda1)) ^ 2.0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $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) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{{\cos \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
Taylor expanded in phi1 around 0 47.3%
+-commutative47.3%
associate--r+47.3%
unpow247.3%
1-sub-sin47.4%
unpow247.4%
*-commutative47.4%
unpow247.4%
unpow247.4%
Simplified47.4%
Taylor expanded in phi2 around 0 32.7%
sub-neg32.7%
mul-1-neg32.7%
unpow232.7%
1-sub-sin32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
distribute-lft-in32.7%
+-commutative32.7%
sub-neg32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
Simplified32.7%
Taylor expanded in lambda2 around 0 28.8%
unpow228.8%
1-sub-sin28.8%
unpow228.8%
Simplified28.8%
Final simplification28.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (/ (+ 1.0 (cos lambda1)) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 + cos(lambda1)) / 2.0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 + cos(lambda1)) / 2.0d0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 + Math.cos(lambda1)) / 2.0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 + math.cos(lambda1)) / 2.0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 + cos(lambda1)) / 2.0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 + cos(lambda1)) / 2.0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[Cos[lambda1], $MachinePrecision]), $MachinePrecision] / 2.0), $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) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\frac{1 + \cos \lambda_1}{2}}}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
Taylor expanded in phi1 around 0 47.3%
+-commutative47.3%
associate--r+47.3%
unpow247.3%
1-sub-sin47.4%
unpow247.4%
*-commutative47.4%
unpow247.4%
unpow247.4%
Simplified47.4%
Taylor expanded in phi2 around 0 32.7%
sub-neg32.7%
mul-1-neg32.7%
unpow232.7%
1-sub-sin32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
distribute-lft-in32.7%
+-commutative32.7%
sub-neg32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
Simplified32.7%
Taylor expanded in lambda2 around 0 28.8%
unpow228.8%
1-sub-sin28.8%
unpow228.8%
Simplified28.8%
unpow228.8%
cos-mult28.8%
Applied egg-rr28.8%
+-commutative28.8%
+-inverses28.8%
cos-028.8%
distribute-rgt-out28.8%
metadata-eval28.8%
*-rgt-identity28.8%
Simplified28.8%
Final simplification28.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (- 0.5 (/ (cos (- lambda1 lambda2)) 2.0)))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (pow (cos (* 0.5 lambda1)) 2.0))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5 - (cos((lambda1 - lambda2)) / 2.0))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(pow(cos((0.5 * lambda1)), 2.0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5d0 - (cos((lambda1 - lambda2)) / 2.0d0))) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((cos((0.5d0 * lambda1)) ** 2.0d0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (0.5 - (Math.cos((lambda1 - lambda2)) / 2.0))) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(Math.pow(Math.cos((0.5 * lambda1)), 2.0))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (0.5 - (math.cos((lambda1 - lambda2)) / 2.0))) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(math.pow(math.cos((0.5 * lambda1)), 2.0))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) / 2.0))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((cos(Float64(0.5 * lambda1)) ^ 2.0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5 - (cos((lambda1 - lambda2)) / 2.0))) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((cos((0.5 * lambda1)) ^ 2.0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{{\cos \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
Taylor expanded in phi1 around 0 47.3%
+-commutative47.3%
associate--r+47.3%
unpow247.3%
1-sub-sin47.4%
unpow247.4%
*-commutative47.4%
unpow247.4%
unpow247.4%
Simplified47.4%
Taylor expanded in phi2 around 0 32.7%
sub-neg32.7%
mul-1-neg32.7%
unpow232.7%
1-sub-sin32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
distribute-lft-in32.7%
+-commutative32.7%
sub-neg32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
Simplified32.7%
Taylor expanded in lambda2 around 0 28.8%
unpow228.8%
1-sub-sin28.8%
unpow228.8%
Simplified28.8%
sin-mult80.6%
cos-sum80.6%
cos-280.6%
div-sub80.6%
+-inverses80.6%
Applied egg-rr26.8%
cos-080.6%
metadata-eval80.6%
Simplified26.8%
Final simplification26.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
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)) + pow(sin(((phi1 - phi2) / 2.0)), 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)) + (sin(((phi1 - phi2) / 2.0d0)) ** 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)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 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)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 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)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 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)) + (sin(((phi1 - phi2) / 2.0)) ^ 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[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / 1.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{1}\right)
\end{array}
\end{array}
Initial program 62.5%
associate-*l*62.5%
Simplified62.6%
Taylor expanded in phi1 around 0 47.3%
+-commutative47.3%
associate--r+47.3%
unpow247.3%
1-sub-sin47.4%
unpow247.4%
*-commutative47.4%
unpow247.4%
unpow247.4%
Simplified47.4%
Taylor expanded in phi2 around 0 32.7%
sub-neg32.7%
mul-1-neg32.7%
unpow232.7%
1-sub-sin32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
distribute-lft-in32.7%
+-commutative32.7%
sub-neg32.7%
distribute-lft-in32.7%
metadata-eval32.7%
associate-*r*32.7%
neg-mul-132.7%
associate-*r*32.7%
metadata-eval32.7%
Simplified32.7%
Taylor expanded in lambda2 around 0 28.8%
unpow228.8%
1-sub-sin28.8%
unpow228.8%
Simplified28.8%
Taylor expanded in lambda1 around 0 23.9%
Final simplification23.9%
herbie shell --seed 2024091
(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))))))))))