
(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 25 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 (/ (- lambda1 lambda2) 2.0)))
(t_1
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))
(t_2 (sqrt (+ (* t_0 (* (* (cos phi1) (cos phi2)) t_0)) t_1))))
(if (or (<= lambda1 -0.000108) (not (<= lambda1 1.7e-6)))
(*
R
(*
2.0
(atan2
t_2
(sqrt
(-
1.0
(+
t_1
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0)))))))))
(*
R
(*
2.0
(atan2
t_2
(sqrt
(-
1.0
(+
t_1
(*
(cos phi1)
(* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double t_2 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + t_1));
double tmp;
if ((lambda1 <= -0.000108) || !(lambda1 <= 1.7e-6)) {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - (t_1 + (cos(phi1) * (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))))))));
} else {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - (t_1 + (cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = ((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
t_2 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + t_1))
if ((lambda1 <= (-0.000108d0)) .or. (.not. (lambda1 <= 1.7d-6))) then
tmp = r * (2.0d0 * atan2(t_2, sqrt((1.0d0 - (t_1 + (cos(phi1) * (cos(phi2) * (sin((lambda1 * 0.5d0)) ** 2.0d0))))))))
else
tmp = r * (2.0d0 * atan2(t_2, sqrt((1.0d0 - (t_1 + (cos(phi1) * (cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0))))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
double t_2 = Math.sqrt(((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + t_1));
double tmp;
if ((lambda1 <= -0.000108) || !(lambda1 <= 1.7e-6)) {
tmp = R * (2.0 * Math.atan2(t_2, Math.sqrt((1.0 - (t_1 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda1 * 0.5)), 2.0))))))));
} 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((lambda2 * -0.5)), 2.0))))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) t_2 = math.sqrt(((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + t_1)) tmp = 0 if (lambda1 <= -0.000108) or not (lambda1 <= 1.7e-6): tmp = R * (2.0 * math.atan2(t_2, math.sqrt((1.0 - (t_1 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda1 * 0.5)), 2.0)))))))) 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((lambda2 * -0.5)), 2.0)))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_2 = sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + t_1)) tmp = 0.0 if ((lambda1 <= -0.000108) || !(lambda1 <= 1.7e-6)) tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - Float64(t_1 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))))))))); 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(lambda2 * -0.5)) ^ 2.0))))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = ((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; t_2 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + t_1)); tmp = 0.0; if ((lambda1 <= -0.000108) || ~((lambda1 <= 1.7e-6))) tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - (t_1 + (cos(phi1) * (cos(phi2) * (sin((lambda1 * 0.5)) ^ 2.0)))))))); else tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - (t_1 + (cos(phi1) * (cos(phi2) * (sin((lambda2 * -0.5)) ^ 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[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda1, -0.000108], N[Not[LessEqual[lambda1, 1.7e-6]], $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[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $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[(lambda2 * -0.5), $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(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_2 := \sqrt{t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + t\_1}\\
\mathbf{if}\;\lambda_1 \leq -0.000108 \lor \neg \left(\lambda_1 \leq 1.7 \cdot 10^{-6}\right):\\
\;\;\;\;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(\lambda_1 \cdot 0.5\right)}^{2}\right)\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(\lambda_2 \cdot -0.5\right)}^{2}\right)\right)}}\right)\\
\end{array}
\end{array}
if lambda1 < -1.08e-4 or 1.70000000000000003e-6 < lambda1 Initial program 49.3%
div-sub49.3%
sin-diff50.0%
Applied egg-rr50.0%
fma-neg50.0%
distribute-rgt-neg-in50.0%
Simplified50.0%
div-sub49.3%
sin-diff50.0%
Applied egg-rr62.4%
Taylor expanded in phi1 around inf 62.4%
Taylor expanded in lambda2 around 0 62.4%
if -1.08e-4 < lambda1 < 1.70000000000000003e-6Initial program 80.0%
div-sub80.0%
sin-diff81.1%
Applied egg-rr81.1%
fma-neg81.1%
distribute-rgt-neg-in81.1%
Simplified81.1%
div-sub80.0%
sin-diff81.1%
Applied egg-rr98.1%
Taylor expanded in phi1 around inf 98.1%
Taylor expanded in lambda1 around 0 98.1%
Final simplification81.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (/ phi2 2.0)))
(t_1 (sin (/ phi2 2.0)))
(t_2 (cos (/ phi1 2.0)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* t_3 (* (* (cos phi1) (cos phi2)) t_3)))
(t_5 (sin (/ phi1 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_5 t_0 (* t_1 (- t_2))) 2.0) t_4))
(sqrt (- 1.0 (+ t_4 (pow (- (* t_5 t_0) (* t_2 t_1)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi2 / 2.0));
double t_1 = sin((phi2 / 2.0));
double t_2 = cos((phi1 / 2.0));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = t_3 * ((cos(phi1) * cos(phi2)) * t_3);
double t_5 = sin((phi1 / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(t_5, t_0, (t_1 * -t_2)), 2.0) + t_4)), sqrt((1.0 - (t_4 + pow(((t_5 * t_0) - (t_2 * t_1)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi2 / 2.0)) t_1 = sin(Float64(phi2 / 2.0)) t_2 = cos(Float64(phi1 / 2.0)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(t_3 * Float64(Float64(cos(phi1) * cos(phi2)) * t_3)) t_5 = sin(Float64(phi1 / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_5, t_0, Float64(t_1 * Float64(-t_2))) ^ 2.0) + t_4)), sqrt(Float64(1.0 - Float64(t_4 + (Float64(Float64(t_5 * t_0) - Float64(t_2 * t_1)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$3 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$5 * t$95$0 + N[(t$95$1 * (-t$95$2)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$4 + N[Power[N[(N[(t$95$5 * t$95$0), $MachinePrecision] - N[(t$95$2 * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\frac{\phi_2}{2}\right)\\
t_1 := \sin \left(\frac{\phi_2}{2}\right)\\
t_2 := \cos \left(\frac{\phi_1}{2}\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := t\_3 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_3\right)\\
t_5 := \sin \left(\frac{\phi_1}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_5, t\_0, t\_1 \cdot \left(-t\_2\right)\right)\right)}^{2} + t\_4}}{\sqrt{1 - \left(t\_4 + {\left(t\_5 \cdot t\_0 - t\_2 \cdot t\_1\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.9%
div-sub65.9%
sin-diff66.8%
Applied egg-rr66.8%
fma-neg66.8%
distribute-rgt-neg-in66.8%
Simplified66.8%
div-sub65.9%
sin-diff66.8%
Applied egg-rr81.6%
Final simplification81.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (* t_0 (* t_1 t_0)))
(t_3 (* t_1 (* t_0 t_0)))
(t_4 (cos (/ phi2 2.0)))
(t_5 (sin (/ phi2 2.0)))
(t_6 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_7 (cos (/ phi1 2.0)))
(t_8 (sin (/ phi1 2.0)))
(t_9
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(if (<= lambda1 -5.4e-10)
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 t_6))
(sqrt (- 1.0 (+ (pow (fma t_8 t_4 (* t_5 (- t_7))) 2.0) t_2))))))
(if (<= lambda1 3.6e-6)
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 t_9))
(sqrt
(-
1.0
(+
t_9
(*
(cos phi1)
(* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (- (* t_8 t_4) (* t_7 t_5)) 2.0) t_3))
(sqrt (- (- 1.0 t_6) t_3)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = t_0 * (t_1 * t_0);
double t_3 = t_1 * (t_0 * t_0);
double t_4 = cos((phi2 / 2.0));
double t_5 = sin((phi2 / 2.0));
double t_6 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_7 = cos((phi1 / 2.0));
double t_8 = sin((phi1 / 2.0));
double t_9 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double tmp;
if (lambda1 <= -5.4e-10) {
tmp = R * (2.0 * atan2(sqrt((t_2 + t_6)), sqrt((1.0 - (pow(fma(t_8, t_4, (t_5 * -t_7)), 2.0) + t_2)))));
} else if (lambda1 <= 3.6e-6) {
tmp = R * (2.0 * atan2(sqrt((t_2 + t_9)), sqrt((1.0 - (t_9 + (cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(((t_8 * t_4) - (t_7 * t_5)), 2.0) + t_3)), sqrt(((1.0 - t_6) - t_3))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = Float64(t_0 * Float64(t_1 * t_0)) t_3 = Float64(t_1 * Float64(t_0 * t_0)) t_4 = cos(Float64(phi2 / 2.0)) t_5 = sin(Float64(phi2 / 2.0)) t_6 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_7 = cos(Float64(phi1 / 2.0)) t_8 = sin(Float64(phi1 / 2.0)) t_9 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 tmp = 0.0 if (lambda1 <= -5.4e-10) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + t_6)), sqrt(Float64(1.0 - Float64((fma(t_8, t_4, Float64(t_5 * Float64(-t_7))) ^ 2.0) + t_2)))))); elseif (lambda1 <= 3.6e-6) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + t_9)), sqrt(Float64(1.0 - Float64(t_9 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(t_8 * t_4) - Float64(t_7 * t_5)) ^ 2.0) + t_3)), sqrt(Float64(Float64(1.0 - t_6) - t_3))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$0 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$7 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$8 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$9 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[lambda1, -5.4e-10], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + t$95$6), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(t$95$8 * t$95$4 + N[(t$95$5 * (-t$95$7)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 3.6e-6], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + t$95$9), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$9 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(t$95$8 * t$95$4), $MachinePrecision] - N[(t$95$7 * t$95$5), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$6), $MachinePrecision] - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := t\_0 \cdot \left(t\_1 \cdot t\_0\right)\\
t_3 := t\_1 \cdot \left(t\_0 \cdot t\_0\right)\\
t_4 := \cos \left(\frac{\phi_2}{2}\right)\\
t_5 := \sin \left(\frac{\phi_2}{2}\right)\\
t_6 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_7 := \cos \left(\frac{\phi_1}{2}\right)\\
t_8 := \sin \left(\frac{\phi_1}{2}\right)\\
t_9 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
\mathbf{if}\;\lambda_1 \leq -5.4 \cdot 10^{-10}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_6}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(t\_8, t\_4, t\_5 \cdot \left(-t\_7\right)\right)\right)}^{2} + t\_2\right)}}\right)\\
\mathbf{elif}\;\lambda_1 \leq 3.6 \cdot 10^{-6}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_9}}{\sqrt{1 - \left(t\_9 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(t\_8 \cdot t\_4 - t\_7 \cdot t\_5\right)}^{2} + t\_3}}{\sqrt{\left(1 - t\_6\right) - t\_3}}\right)\\
\end{array}
\end{array}
if lambda1 < -5.4e-10Initial program 48.9%
div-sub48.9%
sin-diff49.6%
Applied egg-rr50.0%
fma-neg49.6%
distribute-rgt-neg-in49.6%
Simplified50.0%
if -5.4e-10 < lambda1 < 3.59999999999999984e-6Initial program 79.7%
div-sub79.7%
sin-diff80.8%
Applied egg-rr80.8%
fma-neg80.8%
distribute-rgt-neg-in80.8%
Simplified80.8%
div-sub79.7%
sin-diff80.8%
Applied egg-rr98.4%
Taylor expanded in phi1 around inf 98.4%
Taylor expanded in lambda1 around 0 98.2%
if 3.59999999999999984e-6 < lambda1 Initial program 50.3%
associate-*l*50.3%
Simplified50.3%
div-sub50.3%
sin-diff51.0%
Applied egg-rr51.0%
Final simplification76.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_1
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(sqrt
(-
1.0
(+
t_1
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0))), sqrt((1.0 - (t_1 + pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0))), sqrt((1.0d0 - (t_1 + (((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0))), Math.sqrt((1.0 - (t_1 + Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0))), math.sqrt((1.0 - (t_1 + math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_1 + (Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0))), sqrt((1.0 - (t_1 + (((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}}}{\sqrt{1 - \left(t\_1 + {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.9%
div-sub65.9%
sin-diff66.8%
Applied egg-rr66.8%
fma-neg66.8%
distribute-rgt-neg-in66.8%
Simplified66.8%
div-sub65.9%
sin-diff66.8%
Applied egg-rr81.6%
Taylor expanded in phi1 around inf 81.6%
Final simplification81.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* (* (cos phi1) (cos phi2)) t_1)) t_0))
(sqrt
(-
1.0
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt(((t_1 * ((cos(phi1) * cos(phi2)) * t_1)) + t_0)), sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0))) + t_0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = ((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((t_1 * ((cos(phi1) * cos(phi2)) * t_1)) + t_0)), sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0))) + t_0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt(((t_1 * ((Math.cos(phi1) * Math.cos(phi2)) * t_1)) + t_0)), Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt(((t_1 * ((math.cos(phi1) * math.cos(phi2)) * t_1)) + t_0)), math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)) + t_0)), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))) + t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((t_1 * ((cos(phi1) * cos(phi2)) * t_1)) + t_0)), sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0))) + t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + 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[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) + t\_0}}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right) + t\_0\right)}}\right)
\end{array}
\end{array}
Initial program 65.9%
div-sub65.9%
sin-diff66.8%
Applied egg-rr66.8%
fma-neg66.8%
distribute-rgt-neg-in66.8%
Simplified66.8%
div-sub65.9%
sin-diff66.8%
Applied egg-rr81.6%
Taylor expanded in phi1 around inf 81.6%
Taylor expanded in phi1 around inf 81.6%
Final simplification81.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(fma
(sin (/ phi1 2.0))
(cos (/ phi2 2.0))
(* (sin (/ phi2 2.0)) (- (cos (/ phi1 2.0)))))
2.0)
t_1))
(sqrt (- 1.0 (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((pow(fma(sin((phi1 / 2.0)), cos((phi2 / 2.0)), (sin((phi2 / 2.0)) * -cos((phi1 / 2.0)))), 2.0) + t_1)), sqrt((1.0 - (t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(sin(Float64(phi1 / 2.0)), cos(Float64(phi2 / 2.0)), Float64(sin(Float64(phi2 / 2.0)) * Float64(-cos(Float64(phi1 / 2.0))))) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision] * (-N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision])), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\sin \left(\frac{\phi_1}{2}\right), \cos \left(\frac{\phi_2}{2}\right), \sin \left(\frac{\phi_2}{2}\right) \cdot \left(-\cos \left(\frac{\phi_1}{2}\right)\right)\right)\right)}^{2} + t\_1}}{\sqrt{1 - \left(t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.9%
div-sub65.9%
sin-diff66.8%
Applied egg-rr66.8%
fma-neg66.8%
distribute-rgt-neg-in66.8%
Simplified66.8%
Final simplification66.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(+
t_1
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (t_1 + pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (t_1 + (((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - (t_1 + Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - (t_1 + math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_1 + (Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (t_1 + (((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \left(t\_1 + {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.9%
div-sub65.9%
sin-diff66.8%
Applied egg-rr66.6%
Final simplification66.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)
t_1))
(sqrt (- (- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0) + t_1)), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt(((((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0) + t_1)), sqrt(((1.0d0 - (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0) + t_1)), Math.sqrt(((1.0 - Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) + t_1)), math.sqrt(((1.0 - math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0) + t_1)), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt(((((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0) + t_1)), sqrt(((1.0 - (sin(((phi1 - phi2) / 2.0)) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2} + t\_1}}{\sqrt{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 65.9%
associate-*l*65.9%
Simplified65.9%
div-sub65.9%
sin-diff66.8%
Applied egg-rr66.8%
Final simplification66.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_1))))
(sqrt
(fabs
(+
-1.0
(fma
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
t_0
(pow (sin (* -0.5 (- phi2 phi1))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_1)))), sqrt(fabs((-1.0 + fma((0.5 + (-0.5 * cos((lambda1 - lambda2)))), t_0, pow(sin((-0.5 * (phi2 - phi1))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_1)))), sqrt(abs(Float64(-1.0 + fma(Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), t_0, (sin(Float64(-0.5 * Float64(phi2 - phi1))) ^ 2.0)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(-1.0 + N[(N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left|-1 + \mathsf{fma}\left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_0, {\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 65.9%
associate-*l*65.9%
Simplified65.9%
Applied egg-rr66.1%
Simplified66.1%
Final simplification66.1%
(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
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_1 t_1))))))
(if (or (<= phi1 -8e-7) (not (<= phi1 3.8e-15)))
(*
R
(*
2.0
(atan2 t_2 (sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) t_0))))))
(*
R
(*
2.0
(atan2
t_2
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0)))))))))
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 = sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_1 * t_1))));
double tmp;
if ((phi1 <= -8e-7) || !(phi1 <= 3.8e-15)) {
tmp = R * (2.0 * atan2(t_2, sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * t_0)))));
} else {
tmp = R * (2.0 * atan2(t_2, sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * 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) * (lambda2 - lambda1))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_1 * t_1))))
if ((phi1 <= (-8d-7)) .or. (.not. (phi1 <= 3.8d-15))) then
tmp = r * (2.0d0 * atan2(t_2, sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (cos(phi1) * t_0)))))
else
tmp = r * (2.0d0 * atan2(t_2, sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * 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 * (lambda2 - lambda1))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1))));
double tmp;
if ((phi1 <= -8e-7) || !(phi1 <= 3.8e-15)) {
tmp = R * (2.0 * Math.atan2(t_2, Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (Math.cos(phi1) * t_0)))));
} else {
tmp = R * (2.0 * Math.atan2(t_2, Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * t_0)))));
}
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.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1)))) tmp = 0 if (phi1 <= -8e-7) or not (phi1 <= 3.8e-15): tmp = R * (2.0 * math.atan2(t_2, math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (math.cos(phi1) * t_0))))) else: tmp = R * (2.0 * math.atan2(t_2, math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * t_0))))) 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 = sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)))) tmp = 0.0 if ((phi1 <= -8e-7) || !(phi1 <= 3.8e-15)) tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_0)))))); 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 = sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_1 * t_1)))); tmp = 0.0; if ((phi1 <= -8e-7) || ~((phi1 <= 3.8e-15))) tmp = R * (2.0 * atan2(t_2, sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (cos(phi1) * t_0))))); else tmp = R * (2.0 * atan2(t_2, sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * t_0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(-0.5 * N[(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[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -8e-7], N[Not[LessEqual[phi1, 3.8e-15]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$2 / 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]], $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 := \sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)}\\
\mathbf{if}\;\phi_1 \leq -8 \cdot 10^{-7} \lor \neg \left(\phi_1 \leq 3.8 \cdot 10^{-15}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_0}}\right)\\
\end{array}
\end{array}
if phi1 < -7.9999999999999996e-7 or 3.8000000000000002e-15 < phi1 Initial program 49.0%
associate-*l*49.0%
Simplified49.0%
Taylor expanded in phi2 around 0 49.6%
+-commutative49.6%
associate--r+49.6%
unpow249.6%
1-sub-sin49.7%
unpow249.7%
*-commutative49.7%
Simplified49.7%
if -7.9999999999999996e-7 < phi1 < 3.8000000000000002e-15Initial program 81.2%
associate-*l*81.2%
Simplified81.2%
Taylor expanded in phi1 around 0 81.2%
+-commutative81.2%
associate--r+81.2%
unpow281.2%
1-sub-sin81.2%
unpow281.2%
sub-neg81.2%
mul-1-neg81.2%
distribute-lft-in81.2%
metadata-eval81.2%
associate-*r*81.2%
associate-*r*81.2%
metadata-eval81.2%
distribute-lft-in81.2%
+-commutative81.2%
Simplified81.2%
Final simplification66.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_1))))
(sqrt
(+
(- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(* t_0 (- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)) + (t_0 * ((0.5 * cos((lambda1 - lambda2))) - 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
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_1 * t_1)))), sqrt(((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)) + (t_0 * ((0.5d0 * cos((lambda1 - lambda2))) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_1)))), Math.sqrt(((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)) + (t_0 * ((0.5 * Math.cos((lambda1 - lambda2))) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_1)))), math.sqrt(((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)) + (t_0 * ((0.5 * math.cos((lambda1 - lambda2))) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_1)))), sqrt(Float64(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) + Float64(t_0 * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0)) + (t_0 * ((0.5 * cos((lambda1 - lambda2))) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$0 * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left(1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) + t\_0 \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 65.9%
associate-*l*65.9%
Simplified65.9%
cancel-sign-sub-inv65.9%
div-inv65.9%
metadata-eval65.9%
sqr-sin-a65.9%
cos-265.9%
cos-sum65.9%
add-log-exp20.9%
add-log-exp20.9%
sum-log20.9%
exp-sqrt20.9%
exp-sqrt20.9%
Applied egg-rr65.9%
Final simplification65.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt
(-
(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((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_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(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), 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.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * 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))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt((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((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_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(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_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[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[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{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{{\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 65.9%
associate-*l*65.9%
Simplified65.9%
Taylor expanded in phi1 around 0 52.5%
+-commutative52.5%
associate--r+52.5%
unpow252.5%
1-sub-sin52.5%
unpow252.5%
sub-neg52.5%
mul-1-neg52.5%
distribute-lft-in52.5%
metadata-eval52.5%
associate-*r*52.5%
associate-*r*52.5%
metadata-eval52.5%
distribute-lft-in52.5%
+-commutative52.5%
Simplified52.5%
Final simplification52.5%
(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 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi1) (cos phi2))))
(if (<= R 4.45e-13)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_2 (- 0.5 (/ (cos (- lambda1 lambda2)) 2.0)))))
t_0)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_2 (* t_1 t_1)) (/ (- 1.0 (cos (- phi1 phi2))) 2.0)))
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 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if (R <= 4.45e-13) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_2 * (0.5 - (cos((lambda1 - lambda2)) / 2.0))))), t_0));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_2 * (t_1 * t_1)) + ((1.0 - cos((phi1 - phi2))) / 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 = sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = cos(phi1) * cos(phi2)
if (r <= 4.45d-13) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_2 * (0.5d0 - (cos((lambda1 - lambda2)) / 2.0d0))))), t_0))
else
tmp = r * (2.0d0 * atan2(sqrt(((t_2 * (t_1 * t_1)) + ((1.0d0 - cos((phi1 - phi2))) / 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.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.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.cos(phi1) * Math.cos(phi2);
double tmp;
if (R <= 4.45e-13) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_2 * (0.5 - (Math.cos((lambda1 - lambda2)) / 2.0))))), t_0));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_2 * (t_1 * t_1)) + ((1.0 - Math.cos((phi1 - phi2))) / 2.0))), 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.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.cos(phi1) * math.cos(phi2) tmp = 0 if R <= 4.45e-13: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_2 * (0.5 - (math.cos((lambda1 - lambda2)) / 2.0))))), t_0)) else: tmp = R * (2.0 * math.atan2(math.sqrt(((t_2 * (t_1 * t_1)) + ((1.0 - math.cos((phi1 - phi2))) / 2.0))), 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 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if (R <= 4.45e-13) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_2 * Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) / 2.0))))), t_0))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_2 * Float64(t_1 * t_1)) + Float64(Float64(1.0 - cos(Float64(phi1 - phi2))) / 2.0))), 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 = sin(((lambda1 - lambda2) / 2.0)); t_2 = cos(phi1) * cos(phi2); tmp = 0.0; if (R <= 4.45e-13) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_2 * (0.5 - (cos((lambda1 - lambda2)) / 2.0))))), t_0)); else tmp = R * (2.0 * atan2(sqrt(((t_2 * (t_1 * t_1)) + ((1.0 - cos((phi1 - phi2))) / 2.0))), 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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[R, 4.45e-13], 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$2 * N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(N[(1.0 - N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / 2.0), $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 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;R \leq 4.45 \cdot 10^{-13}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_2 \cdot \left(0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}\right)}}{t\_0}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 \cdot \left(t\_1 \cdot t\_1\right) + \frac{1 - \cos \left(\phi_1 - \phi_2\right)}{2}}}{t\_0}\right)\\
\end{array}
\end{array}
if R < 4.4500000000000002e-13Initial program 65.0%
associate-*l*65.0%
Simplified65.0%
Taylor expanded in phi1 around 0 52.6%
+-commutative52.6%
associate--r+52.6%
unpow252.6%
1-sub-sin52.7%
unpow252.7%
sub-neg52.7%
mul-1-neg52.7%
distribute-lft-in52.7%
metadata-eval52.7%
associate-*r*52.7%
associate-*r*52.7%
metadata-eval52.7%
distribute-lft-in52.7%
+-commutative52.7%
Simplified52.7%
sin-mult34.6%
div-inv34.6%
metadata-eval34.6%
div-inv34.6%
metadata-eval34.6%
cos-sum34.5%
cos-234.6%
div-inv34.6%
metadata-eval34.6%
Applied egg-rr50.9%
div-sub34.6%
+-inverses34.6%
cos-034.6%
metadata-eval34.6%
*-commutative34.6%
associate-*r*34.6%
metadata-eval34.6%
Simplified50.9%
if 4.4500000000000002e-13 < R Initial program 68.6%
associate-*l*68.6%
Simplified68.5%
Taylor expanded in phi1 around 0 52.1%
+-commutative52.1%
associate--r+52.1%
unpow252.1%
1-sub-sin52.1%
unpow252.1%
sub-neg52.1%
mul-1-neg52.1%
distribute-lft-in52.1%
metadata-eval52.1%
associate-*r*52.1%
associate-*r*52.1%
metadata-eval52.1%
distribute-lft-in52.1%
+-commutative52.1%
Simplified52.1%
unpow237.0%
sin-mult36.4%
div-inv36.4%
metadata-eval36.4%
div-inv36.4%
metadata-eval36.4%
div-inv36.4%
metadata-eval36.4%
div-inv36.4%
metadata-eval36.4%
Applied egg-rr51.4%
+-inverses36.4%
cos-036.4%
distribute-lft-out36.4%
metadata-eval36.4%
*-rgt-identity36.4%
Simplified51.4%
Final simplification51.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* -0.5 (- lambda2 lambda1)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (cos t_0)))
(if (or (<= phi2 -115000.0) (not (<= phi2 160000000.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))
(pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin t_0) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_1 t_1))))
(sqrt (* t_2 t_2))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = -0.5 * (lambda2 - lambda1);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(t_0);
double tmp;
if ((phi2 <= -115000.0) || !(phi2 <= 160000000.0)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0)) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin(t_0), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_1 * t_1)))), sqrt((t_2 * t_2))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = (-0.5d0) * (lambda2 - lambda1)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = cos(t_0)
if ((phi2 <= (-115000.0d0)) .or. (.not. (phi2 <= 160000000.0d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0)) + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (sin(t_0) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_1 * t_1)))), sqrt((t_2 * t_2))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = -0.5 * (lambda2 - lambda1);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.cos(t_0);
double tmp;
if ((phi2 <= -115000.0) || !(phi2 <= 160000000.0)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0)) + 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(t_0), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1)))), Math.sqrt((t_2 * t_2))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = -0.5 * (lambda2 - lambda1) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.cos(t_0) tmp = 0 if (phi2 <= -115000.0) or not (phi2 <= 160000000.0): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0)) + 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(t_0), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1)))), math.sqrt((t_2 * t_2)))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(-0.5 * Float64(lambda2 - lambda1)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = cos(t_0) tmp = 0.0 if ((phi2 <= -115000.0) || !(phi2 <= 160000000.0)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(t_0) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)))), sqrt(Float64(t_2 * t_2))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = -0.5 * (lambda2 - lambda1); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = cos(t_0); tmp = 0.0; if ((phi2 <= -115000.0) || ~((phi2 <= 160000000.0))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0)) + (sin((phi2 * -0.5)) ^ 2.0))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (sin(t_0) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_1 * t_1)))), sqrt((t_2 * t_2)))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[t$95$0], $MachinePrecision]}, If[Or[LessEqual[phi2, -115000.0], N[Not[LessEqual[phi2, 160000000.0]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(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[t$95$0], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$2 * t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := -0.5 \cdot \left(\lambda_2 - \lambda_1\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos t\_0\\
\mathbf{if}\;\phi_2 \leq -115000 \lor \neg \left(\phi_2 \leq 160000000\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{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 t\_0}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{t\_2 \cdot t\_2}}\right)\\
\end{array}
\end{array}
if phi2 < -115000 or 1.6e8 < phi2 Initial program 46.8%
associate-*l*46.8%
Simplified46.8%
Taylor expanded in phi1 around 0 47.2%
+-commutative47.2%
associate--r+47.2%
unpow247.2%
1-sub-sin47.3%
unpow247.3%
sub-neg47.3%
mul-1-neg47.3%
distribute-lft-in47.3%
metadata-eval47.3%
associate-*r*47.3%
associate-*r*47.3%
metadata-eval47.3%
distribute-lft-in47.3%
+-commutative47.3%
Simplified47.3%
Taylor expanded in lambda1 around 0 43.6%
*-commutative43.6%
Simplified43.6%
Taylor expanded in phi1 around 0 44.2%
if -115000 < phi2 < 1.6e8Initial program 80.2%
associate-*l*80.2%
Simplified80.2%
Taylor expanded in phi1 around 0 56.5%
+-commutative56.5%
associate--r+56.5%
unpow256.5%
1-sub-sin56.5%
unpow256.5%
sub-neg56.5%
mul-1-neg56.5%
distribute-lft-in56.5%
metadata-eval56.5%
associate-*r*56.5%
associate-*r*56.5%
metadata-eval56.5%
distribute-lft-in56.5%
+-commutative56.5%
Simplified56.5%
Taylor expanded in phi2 around 0 55.0%
unpow255.0%
1-sub-sin55.1%
Applied egg-rr55.1%
Final simplification50.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (- 0.5 (/ (cos (- lambda1 lambda2)) 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) {
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (0.5 - (cos((lambda1 - lambda2)) / 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
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (0.5d0 - (cos((lambda1 - lambda2)) / 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) {
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (0.5 - (Math.cos((lambda1 - lambda2)) / 2.0))))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (0.5 - (math.cos((lambda1 - lambda2)) / 2.0))))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) / 2.0))))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (0.5 - (cos((lambda1 - lambda2)) / 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_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $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[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}\right)}}{\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}
Initial program 65.9%
associate-*l*65.9%
Simplified65.9%
Taylor expanded in phi1 around 0 52.5%
+-commutative52.5%
associate--r+52.5%
unpow252.5%
1-sub-sin52.5%
unpow252.5%
sub-neg52.5%
mul-1-neg52.5%
distribute-lft-in52.5%
metadata-eval52.5%
associate-*r*52.5%
associate-*r*52.5%
metadata-eval52.5%
distribute-lft-in52.5%
+-commutative52.5%
Simplified52.5%
sin-mult33.7%
div-inv33.7%
metadata-eval33.7%
div-inv33.7%
metadata-eval33.7%
cos-sum33.6%
cos-233.7%
div-inv33.7%
metadata-eval33.7%
Applied egg-rr49.7%
div-sub33.7%
+-inverses33.7%
cos-033.7%
metadata-eval33.7%
*-commutative33.7%
associate-*r*33.7%
metadata-eval33.7%
Simplified49.7%
Final simplification49.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (pow (sin (* lambda2 -0.5)) 2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_0 (* t_2 t_2)))
(t_4 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (<= lambda2 -15000.0)
(*
R
(*
2.0
(atan2
(sqrt (+ t_3 (/ (- 1.0 (cos (- phi1 phi2))) 2.0)))
(sqrt (- 1.0 t_1)))))
(if (<= lambda2 2.8e-43)
(*
R
(*
2.0
(atan2 (sqrt (+ t_4 t_3)) (sqrt (pow (cos (* lambda1 0.5)) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_4 (* t_0 t_1)))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(sin((lambda2 * -0.5)), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_0 * (t_2 * t_2);
double t_4 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (lambda2 <= -15000.0) {
tmp = R * (2.0 * atan2(sqrt((t_3 + ((1.0 - cos((phi1 - phi2))) / 2.0))), sqrt((1.0 - t_1))));
} else if (lambda2 <= 2.8e-43) {
tmp = R * (2.0 * atan2(sqrt((t_4 + t_3)), sqrt(pow(cos((lambda1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_4 + (t_0 * t_1))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - 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) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = cos(phi1) * cos(phi2)
t_1 = sin((lambda2 * (-0.5d0))) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = t_0 * (t_2 * t_2)
t_4 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
if (lambda2 <= (-15000.0d0)) then
tmp = r * (2.0d0 * atan2(sqrt((t_3 + ((1.0d0 - cos((phi1 - phi2))) / 2.0d0))), sqrt((1.0d0 - t_1))))
else if (lambda2 <= 2.8d-43) then
tmp = r * (2.0d0 * atan2(sqrt((t_4 + t_3)), sqrt((cos((lambda1 * 0.5d0)) ** 2.0d0))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_4 + (t_0 * t_1))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - 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.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(Math.sin((lambda2 * -0.5)), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_0 * (t_2 * t_2);
double t_4 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (lambda2 <= -15000.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + ((1.0 - Math.cos((phi1 - phi2))) / 2.0))), Math.sqrt((1.0 - t_1))));
} else if (lambda2 <= 2.8e-43) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_4 + t_3)), Math.sqrt(Math.pow(Math.cos((lambda1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_4 + (t_0 * t_1))), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(math.sin((lambda2 * -0.5)), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = t_0 * (t_2 * t_2) t_4 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) tmp = 0 if lambda2 <= -15000.0: tmp = R * (2.0 * math.atan2(math.sqrt((t_3 + ((1.0 - math.cos((phi1 - phi2))) / 2.0))), math.sqrt((1.0 - t_1)))) elif lambda2 <= 2.8e-43: tmp = R * (2.0 * math.atan2(math.sqrt((t_4 + t_3)), math.sqrt(math.pow(math.cos((lambda1 * 0.5)), 2.0)))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_4 + (t_0 * t_1))), math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(lambda2 * -0.5)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_0 * Float64(t_2 * t_2)) t_4 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if (lambda2 <= -15000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + Float64(Float64(1.0 - cos(Float64(phi1 - phi2))) / 2.0))), sqrt(Float64(1.0 - t_1))))); elseif (lambda2 <= 2.8e-43) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + t_3)), sqrt((cos(Float64(lambda1 * 0.5)) ^ 2.0))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + Float64(t_0 * t_1))), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin((lambda2 * -0.5)) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = t_0 * (t_2 * t_2); t_4 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = 0.0; if (lambda2 <= -15000.0) tmp = R * (2.0 * atan2(sqrt((t_3 + ((1.0 - cos((phi1 - phi2))) / 2.0))), sqrt((1.0 - t_1)))); elseif (lambda2 <= 2.8e-43) tmp = R * (2.0 * atan2(sqrt((t_4 + t_3)), sqrt((cos((lambda1 * 0.5)) ^ 2.0)))); else tmp = R * (2.0 * atan2(sqrt((t_4 + (t_0 * t_1))), sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[lambda2, -15000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + N[(N[(1.0 - N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda2, 2.8e-43], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_0 \cdot \left(t\_2 \cdot t\_2\right)\\
t_4 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\lambda_2 \leq -15000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + \frac{1 - \cos \left(\phi_1 - \phi_2\right)}{2}}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{elif}\;\lambda_2 \leq 2.8 \cdot 10^{-43}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + t\_3}}{\sqrt{{\cos \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + t\_0 \cdot t\_1}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if lambda2 < -15000Initial program 57.5%
associate-*l*57.5%
Simplified57.5%
Taylor expanded in phi1 around 0 44.3%
+-commutative44.3%
associate--r+44.3%
unpow244.3%
1-sub-sin44.4%
unpow244.4%
sub-neg44.4%
mul-1-neg44.4%
distribute-lft-in44.4%
metadata-eval44.4%
associate-*r*44.4%
associate-*r*44.4%
metadata-eval44.4%
distribute-lft-in44.4%
+-commutative44.4%
Simplified44.4%
Taylor expanded in phi2 around 0 35.1%
unpow235.1%
sin-mult35.1%
div-inv35.1%
metadata-eval35.1%
div-inv35.1%
metadata-eval35.1%
div-inv35.1%
metadata-eval35.1%
div-inv35.1%
metadata-eval35.1%
Applied egg-rr35.1%
+-inverses35.1%
cos-035.1%
distribute-lft-out35.1%
metadata-eval35.1%
*-rgt-identity35.1%
Simplified35.1%
Taylor expanded in lambda1 around 0 35.2%
*-commutative35.2%
Simplified35.2%
if -15000 < lambda2 < 2.7999999999999998e-43Initial program 78.0%
associate-*l*78.0%
Simplified78.1%
Taylor expanded in phi1 around 0 62.9%
+-commutative62.9%
associate--r+62.9%
unpow262.9%
1-sub-sin62.9%
unpow262.9%
sub-neg62.9%
mul-1-neg62.9%
distribute-lft-in62.9%
metadata-eval62.9%
associate-*r*62.9%
associate-*r*62.9%
metadata-eval62.9%
distribute-lft-in62.9%
+-commutative62.9%
Simplified62.9%
Taylor expanded in phi2 around 0 48.3%
Taylor expanded in lambda2 around 0 48.4%
unpow248.4%
1-sub-sin48.4%
unpow248.4%
Simplified48.4%
if 2.7999999999999998e-43 < lambda2 Initial program 52.7%
associate-*l*52.7%
Simplified52.7%
Taylor expanded in phi1 around 0 42.4%
+-commutative42.4%
associate--r+42.4%
unpow242.4%
1-sub-sin42.4%
unpow242.4%
sub-neg42.4%
mul-1-neg42.4%
distribute-lft-in42.4%
metadata-eval42.4%
associate-*r*42.4%
associate-*r*42.4%
metadata-eval42.4%
distribute-lft-in42.4%
+-commutative42.4%
Simplified42.4%
Taylor expanded in lambda1 around 0 42.0%
*-commutative42.0%
Simplified42.0%
Taylor expanded in phi2 around 0 30.7%
Final simplification40.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (sqrt (+ t_0 (* t_1 (* t_2 t_2))))))
(if (<= lambda2 -15000.0)
(* R (* 2.0 (atan2 t_3 (sqrt (pow (cos (* lambda2 -0.5)) 2.0)))))
(if (<= lambda2 2.6e-43)
(* R (* 2.0 (atan2 t_3 (sqrt (pow (cos (* lambda1 0.5)) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* t_1 (pow (sin (* lambda2 -0.5)) 2.0))))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = sqrt((t_0 + (t_1 * (t_2 * t_2))));
double tmp;
if (lambda2 <= -15000.0) {
tmp = R * (2.0 * atan2(t_3, sqrt(pow(cos((lambda2 * -0.5)), 2.0))));
} else if (lambda2 <= 2.6e-43) {
tmp = R * (2.0 * atan2(t_3, sqrt(pow(cos((lambda1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_0 + (t_1 * pow(sin((lambda2 * -0.5)), 2.0)))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - 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) :: t_3
real(8) :: tmp
t_0 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_1 = cos(phi1) * cos(phi2)
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = sqrt((t_0 + (t_1 * (t_2 * t_2))))
if (lambda2 <= (-15000.0d0)) then
tmp = r * (2.0d0 * atan2(t_3, sqrt((cos((lambda2 * (-0.5d0))) ** 2.0d0))))
else if (lambda2 <= 2.6d-43) then
tmp = r * (2.0d0 * atan2(t_3, sqrt((cos((lambda1 * 0.5d0)) ** 2.0d0))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_0 + (t_1 * (sin((lambda2 * (-0.5d0))) ** 2.0d0)))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - 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.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = Math.sqrt((t_0 + (t_1 * (t_2 * t_2))));
double tmp;
if (lambda2 <= -15000.0) {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt(Math.pow(Math.cos((lambda2 * -0.5)), 2.0))));
} else if (lambda2 <= 2.6e-43) {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt(Math.pow(Math.cos((lambda1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + (t_1 * Math.pow(Math.sin((lambda2 * -0.5)), 2.0)))), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_1 = math.cos(phi1) * math.cos(phi2) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = math.sqrt((t_0 + (t_1 * (t_2 * t_2)))) tmp = 0 if lambda2 <= -15000.0: tmp = R * (2.0 * math.atan2(t_3, math.sqrt(math.pow(math.cos((lambda2 * -0.5)), 2.0)))) elif lambda2 <= 2.6e-43: tmp = R * (2.0 * math.atan2(t_3, math.sqrt(math.pow(math.cos((lambda1 * 0.5)), 2.0)))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + (t_1 * math.pow(math.sin((lambda2 * -0.5)), 2.0)))), math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = sqrt(Float64(t_0 + Float64(t_1 * Float64(t_2 * t_2)))) tmp = 0.0 if (lambda2 <= -15000.0) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt((cos(Float64(lambda2 * -0.5)) ^ 2.0))))); elseif (lambda2 <= 2.6e-43) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt((cos(Float64(lambda1 * 0.5)) ^ 2.0))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(t_1 * (sin(Float64(lambda2 * -0.5)) ^ 2.0)))), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_1 = cos(phi1) * cos(phi2); t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = sqrt((t_0 + (t_1 * (t_2 * t_2)))); tmp = 0.0; if (lambda2 <= -15000.0) tmp = R * (2.0 * atan2(t_3, sqrt((cos((lambda2 * -0.5)) ^ 2.0)))); elseif (lambda2 <= 2.6e-43) tmp = R * (2.0 * atan2(t_3, sqrt((cos((lambda1 * 0.5)) ^ 2.0)))); else tmp = R * (2.0 * atan2(sqrt((t_0 + (t_1 * (sin((lambda2 * -0.5)) ^ 2.0)))), sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(t$95$0 + N[(t$95$1 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda2, -15000.0], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[Power[N[Cos[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda2, 2.6e-43], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[Power[N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(t$95$1 * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \sqrt{t\_0 + t\_1 \cdot \left(t\_2 \cdot t\_2\right)}\\
\mathbf{if}\;\lambda_2 \leq -15000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{{\cos \left(\lambda_2 \cdot -0.5\right)}^{2}}}\right)\\
\mathbf{elif}\;\lambda_2 \leq 2.6 \cdot 10^{-43}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{{\cos \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_1 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if lambda2 < -15000Initial program 57.5%
associate-*l*57.5%
Simplified57.5%
Taylor expanded in phi1 around 0 44.3%
+-commutative44.3%
associate--r+44.3%
unpow244.3%
1-sub-sin44.4%
unpow244.4%
sub-neg44.4%
mul-1-neg44.4%
distribute-lft-in44.4%
metadata-eval44.4%
associate-*r*44.4%
associate-*r*44.4%
metadata-eval44.4%
distribute-lft-in44.4%
+-commutative44.4%
Simplified44.4%
Taylor expanded in phi2 around 0 35.1%
Taylor expanded in lambda1 around 0 35.2%
unpow235.2%
1-sub-sin35.3%
unpow235.3%
*-commutative35.3%
Simplified35.3%
if -15000 < lambda2 < 2.6e-43Initial program 78.0%
associate-*l*78.0%
Simplified78.1%
Taylor expanded in phi1 around 0 62.9%
+-commutative62.9%
associate--r+62.9%
unpow262.9%
1-sub-sin62.9%
unpow262.9%
sub-neg62.9%
mul-1-neg62.9%
distribute-lft-in62.9%
metadata-eval62.9%
associate-*r*62.9%
associate-*r*62.9%
metadata-eval62.9%
distribute-lft-in62.9%
+-commutative62.9%
Simplified62.9%
Taylor expanded in phi2 around 0 48.3%
Taylor expanded in lambda2 around 0 48.4%
unpow248.4%
1-sub-sin48.4%
unpow248.4%
Simplified48.4%
if 2.6e-43 < lambda2 Initial program 52.7%
associate-*l*52.7%
Simplified52.7%
Taylor expanded in phi1 around 0 42.4%
+-commutative42.4%
associate--r+42.4%
unpow242.4%
1-sub-sin42.4%
unpow242.4%
sub-neg42.4%
mul-1-neg42.4%
distribute-lft-in42.4%
metadata-eval42.4%
associate-*r*42.4%
associate-*r*42.4%
metadata-eval42.4%
distribute-lft-in42.4%
+-commutative42.4%
Simplified42.4%
Taylor expanded in lambda1 around 0 42.0%
*-commutative42.0%
Simplified42.0%
Taylor expanded in phi2 around 0 30.7%
Final simplification40.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3
(sqrt (+ (* t_1 (* t_2 t_2)) (/ (- 1.0 (cos (- phi1 phi2))) 2.0)))))
(if (<= lambda1 -1e-83)
(* R (* 2.0 (atan2 t_3 t_0)))
(if (<= lambda1 3.7e-8)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_1 (pow (sin (* lambda2 -0.5)) 2.0))))
t_0)))
(*
R
(* 2.0 (atan2 t_3 (sqrt (- 1.0 (pow (sin (* lambda1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = sqrt(((t_1 * (t_2 * t_2)) + ((1.0 - cos((phi1 - phi2))) / 2.0)));
double tmp;
if (lambda1 <= -1e-83) {
tmp = R * (2.0 * atan2(t_3, t_0));
} else if (lambda1 <= 3.7e-8) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * pow(sin((lambda2 * -0.5)), 2.0)))), t_0));
} else {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - pow(sin((lambda1 * 0.5)), 2.0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: tmp
t_0 = sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))
t_1 = cos(phi1) * cos(phi2)
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = sqrt(((t_1 * (t_2 * t_2)) + ((1.0d0 - cos((phi1 - phi2))) / 2.0d0)))
if (lambda1 <= (-1d-83)) then
tmp = r * (2.0d0 * atan2(t_3, t_0))
else if (lambda1 <= 3.7d-8) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_1 * (sin((lambda2 * (-0.5d0))) ** 2.0d0)))), t_0))
else
tmp = r * (2.0d0 * atan2(t_3, sqrt((1.0d0 - (sin((lambda1 * 0.5d0)) ** 2.0d0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = Math.sqrt(((t_1 * (t_2 * t_2)) + ((1.0 - Math.cos((phi1 - phi2))) / 2.0)));
double tmp;
if (lambda1 <= -1e-83) {
tmp = R * (2.0 * Math.atan2(t_3, t_0));
} else if (lambda1 <= 3.7e-8) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * Math.pow(Math.sin((lambda2 * -0.5)), 2.0)))), t_0));
} else {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt((1.0 - Math.pow(Math.sin((lambda1 * 0.5)), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))) t_1 = math.cos(phi1) * math.cos(phi2) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = math.sqrt(((t_1 * (t_2 * t_2)) + ((1.0 - math.cos((phi1 - phi2))) / 2.0))) tmp = 0 if lambda1 <= -1e-83: tmp = R * (2.0 * math.atan2(t_3, t_0)) elif lambda1 <= 3.7e-8: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * math.pow(math.sin((lambda2 * -0.5)), 2.0)))), t_0)) else: tmp = R * (2.0 * math.atan2(t_3, math.sqrt((1.0 - math.pow(math.sin((lambda1 * 0.5)), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = sqrt(Float64(Float64(t_1 * Float64(t_2 * t_2)) + Float64(Float64(1.0 - cos(Float64(phi1 - phi2))) / 2.0))) tmp = 0.0 if (lambda1 <= -1e-83) tmp = Float64(R * Float64(2.0 * atan(t_3, t_0))); elseif (lambda1 <= 3.7e-8) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * (sin(Float64(lambda2 * -0.5)) ^ 2.0)))), t_0))); else tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 - (sin(Float64(lambda1 * 0.5)) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))); t_1 = cos(phi1) * cos(phi2); t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = sqrt(((t_1 * (t_2 * t_2)) + ((1.0 - cos((phi1 - phi2))) / 2.0))); tmp = 0.0; if (lambda1 <= -1e-83) tmp = R * (2.0 * atan2(t_3, t_0)); elseif (lambda1 <= 3.7e-8) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_1 * (sin((lambda2 * -0.5)) ^ 2.0)))), t_0)); else tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - (sin((lambda1 * 0.5)) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[(t$95$1 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(N[(1.0 - N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda1, -1e-83], N[(R * N[(2.0 * N[ArcTan[t$95$3 / t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 3.7e-8], 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[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{1 - {\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(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \sqrt{t\_1 \cdot \left(t\_2 \cdot t\_2\right) + \frac{1 - \cos \left(\phi_1 - \phi_2\right)}{2}}\\
\mathbf{if}\;\lambda_1 \leq -1 \cdot 10^{-83}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{t\_0}\right)\\
\mathbf{elif}\;\lambda_1 \leq 3.7 \cdot 10^{-8}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}}}{t\_0}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if lambda1 < -1e-83Initial program 54.8%
associate-*l*54.8%
Simplified54.8%
Taylor expanded in phi1 around 0 42.9%
+-commutative42.9%
associate--r+42.9%
unpow242.9%
1-sub-sin42.9%
unpow242.9%
sub-neg42.9%
mul-1-neg42.9%
distribute-lft-in42.9%
metadata-eval42.9%
associate-*r*42.9%
associate-*r*42.9%
metadata-eval42.9%
distribute-lft-in42.9%
+-commutative42.9%
Simplified42.9%
Taylor expanded in phi2 around 0 37.6%
unpow237.6%
sin-mult37.6%
div-inv37.6%
metadata-eval37.6%
div-inv37.6%
metadata-eval37.6%
div-inv37.6%
metadata-eval37.6%
div-inv37.6%
metadata-eval37.6%
Applied egg-rr37.6%
+-inverses37.6%
cos-037.6%
distribute-lft-out37.6%
metadata-eval37.6%
*-rgt-identity37.6%
Simplified37.6%
if -1e-83 < lambda1 < 3.7e-8Initial program 80.6%
associate-*l*80.6%
Simplified80.5%
Taylor expanded in phi1 around 0 63.2%
+-commutative63.2%
associate--r+63.2%
unpow263.2%
1-sub-sin63.2%
unpow263.2%
sub-neg63.2%
mul-1-neg63.2%
distribute-lft-in63.2%
metadata-eval63.2%
associate-*r*63.2%
associate-*r*63.2%
metadata-eval63.2%
distribute-lft-in63.2%
+-commutative63.2%
Simplified63.2%
Taylor expanded in lambda1 around 0 62.5%
*-commutative62.5%
Simplified62.5%
Taylor expanded in phi2 around 0 43.6%
if 3.7e-8 < lambda1 Initial program 50.0%
associate-*l*49.9%
Simplified50.0%
Taylor expanded in phi1 around 0 42.7%
+-commutative42.7%
associate--r+42.7%
unpow242.7%
1-sub-sin42.7%
unpow242.7%
sub-neg42.7%
mul-1-neg42.7%
distribute-lft-in42.7%
metadata-eval42.7%
associate-*r*42.7%
associate-*r*42.7%
metadata-eval42.7%
distribute-lft-in42.7%
+-commutative42.7%
Simplified42.7%
Taylor expanded in phi2 around 0 34.6%
unpow234.6%
sin-mult34.6%
div-inv34.6%
metadata-eval34.6%
div-inv34.6%
metadata-eval34.6%
div-inv34.6%
metadata-eval34.6%
div-inv34.6%
metadata-eval34.6%
Applied egg-rr34.6%
+-inverses34.6%
cos-034.6%
distribute-lft-out34.6%
metadata-eval34.6%
*-rgt-identity34.6%
Simplified34.6%
Taylor expanded in lambda2 around 0 34.8%
Final simplification39.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (cos (* -0.5 (- lambda2 lambda1)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt (* t_1 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((-0.5 * (lambda2 - lambda1)));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((t_1 * t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(((-0.5d0) * (lambda2 - lambda1)))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((t_1 * 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((-0.5 * (lambda2 - lambda1)));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)))), Math.sqrt((t_1 * t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos((-0.5 * (lambda2 - lambda1))) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt((t_1 * t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = cos(Float64(-0.5 * Float64(lambda2 - lambda1))) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(t_1 * t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos((-0.5 * (lambda2 - lambda1))); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((t_1 * 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[Cos[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$1 * 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 := \cos \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{t\_1 \cdot t\_1}}\right)
\end{array}
\end{array}
Initial program 65.9%
associate-*l*65.9%
Simplified65.9%
Taylor expanded in phi1 around 0 52.5%
+-commutative52.5%
associate--r+52.5%
unpow252.5%
1-sub-sin52.5%
unpow252.5%
sub-neg52.5%
mul-1-neg52.5%
distribute-lft-in52.5%
metadata-eval52.5%
associate-*r*52.5%
associate-*r*52.5%
metadata-eval52.5%
distribute-lft-in52.5%
+-commutative52.5%
Simplified52.5%
Taylor expanded in phi2 around 0 40.0%
unpow240.0%
1-sub-sin40.1%
Applied egg-rr40.1%
Final simplification40.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt (+ -1.0 (- 2.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 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((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((-1.0 + (2.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt(((-1.0d0) + (2.0d0 - (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)))), Math.sqrt((-1.0 + (2.0 - Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 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.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt((-1.0 + (2.0 - math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 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((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(-1.0 + Float64(2.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((-1.0 + (2.0 - (sin(((lambda1 - lambda2) * 0.5)) ^ 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[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(-1.0 + N[(2.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $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{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{-1 + \left(2 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.9%
associate-*l*65.9%
Simplified65.9%
Taylor expanded in phi1 around 0 52.5%
+-commutative52.5%
associate--r+52.5%
unpow252.5%
1-sub-sin52.5%
unpow252.5%
sub-neg52.5%
mul-1-neg52.5%
distribute-lft-in52.5%
metadata-eval52.5%
associate-*r*52.5%
associate-*r*52.5%
metadata-eval52.5%
distribute-lft-in52.5%
+-commutative52.5%
Simplified52.5%
Taylor expanded in phi2 around 0 40.0%
expm1-log1p-u40.0%
Applied egg-rr40.0%
expm1-undefine40.1%
sub-neg40.1%
Simplified40.0%
Final simplification40.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt (- 1.0 (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((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)))), Math.sqrt((1.0 - 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.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt((1.0 - 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((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(1.0 - (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(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - (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[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 65.9%
associate-*l*65.9%
Simplified65.9%
Taylor expanded in phi1 around 0 52.5%
+-commutative52.5%
associate--r+52.5%
unpow252.5%
1-sub-sin52.5%
unpow252.5%
sub-neg52.5%
mul-1-neg52.5%
distribute-lft-in52.5%
metadata-eval52.5%
associate-*r*52.5%
associate-*r*52.5%
metadata-eval52.5%
distribute-lft-in52.5%
+-commutative52.5%
Simplified52.5%
Taylor expanded in phi2 around 0 40.0%
Final simplification40.0%
(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))))
(if (<= phi2 390000000.0)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_1 t_1))
(/ (- 1.0 (cos phi1)) 2.0)))
(sqrt (- 1.0 t_0)))))
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0)))))))))
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 tmp;
if (phi2 <= 390000000.0) {
tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_1 * t_1)) + ((1.0 - cos(phi1)) / 2.0))), sqrt((1.0 - t_0))));
} else {
tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
if (phi2 <= 390000000.0d0) then
tmp = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_1 * t_1)) + ((1.0d0 - cos(phi1)) / 2.0d0))), sqrt((1.0d0 - t_0))))
else
tmp = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * 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 * (lambda2 - lambda1))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi2 <= 390000000.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1)) + ((1.0 - Math.cos(phi1)) / 2.0))), Math.sqrt((1.0 - t_0))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * t_0)))));
}
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)) tmp = 0 if phi2 <= 390000000.0: tmp = R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1)) + ((1.0 - math.cos(phi1)) / 2.0))), math.sqrt((1.0 - t_0)))) else: tmp = R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * t_0))))) 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)) tmp = 0.0 if (phi2 <= 390000000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) + Float64(Float64(1.0 - cos(phi1)) / 2.0))), sqrt(Float64(1.0 - t_0))))); else tmp = Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_0)))))); 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)); tmp = 0.0; if (phi2 <= 390000000.0) tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_1 * t_1)) + ((1.0 - cos(phi1)) / 2.0))), sqrt((1.0 - t_0)))); else tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * t_0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, 390000000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(N[(1.0 - N[Cos[phi1], $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $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)\\
\mathbf{if}\;\phi_2 \leq 390000000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right) + \frac{1 - \cos \phi_1}{2}}}{\sqrt{1 - t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_0}}\right)\\
\end{array}
\end{array}
if phi2 < 3.9e8Initial program 70.2%
associate-*l*70.2%
Simplified70.2%
Taylor expanded in phi1 around 0 52.9%
+-commutative52.9%
associate--r+52.9%
unpow252.9%
1-sub-sin52.9%
unpow252.9%
sub-neg52.9%
mul-1-neg52.9%
distribute-lft-in52.9%
metadata-eval52.9%
associate-*r*52.9%
associate-*r*52.9%
metadata-eval52.9%
distribute-lft-in52.9%
+-commutative52.9%
Simplified52.9%
Taylor expanded in phi2 around 0 45.5%
unpow245.5%
sin-mult40.9%
div-inv40.9%
metadata-eval40.9%
div-inv40.9%
metadata-eval40.9%
div-inv40.9%
metadata-eval40.9%
div-inv40.9%
metadata-eval40.9%
Applied egg-rr40.9%
+-inverses40.9%
cos-040.9%
distribute-lft-out40.9%
metadata-eval40.9%
*-rgt-identity40.9%
Simplified40.9%
Taylor expanded in phi2 around 0 39.4%
if 3.9e8 < phi2 Initial program 50.7%
associate-*l*50.7%
Simplified50.7%
Taylor expanded in phi1 around 0 51.1%
+-commutative51.1%
associate--r+51.1%
unpow251.1%
1-sub-sin51.1%
unpow251.1%
sub-neg51.1%
mul-1-neg51.1%
distribute-lft-in51.1%
metadata-eval51.1%
associate-*r*51.1%
associate-*r*51.1%
metadata-eval51.1%
distribute-lft-in51.1%
+-commutative51.1%
Simplified51.1%
Taylor expanded in lambda1 around 0 46.1%
*-commutative46.1%
Simplified46.1%
Taylor expanded in lambda2 around 0 21.7%
Final simplification35.4%
(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))
(/ (- 1.0 (cos (- phi1 phi2))) 2.0)))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + ((1.0 - cos((phi1 - phi2))) / 2.0))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
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)) + ((1.0d0 - cos((phi1 - phi2))) / 2.0d0))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
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)) + ((1.0 - Math.cos((phi1 - phi2))) / 2.0))), Math.sqrt((1.0 - 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)) + ((1.0 - math.cos((phi1 - phi2))) / 2.0))), math.sqrt((1.0 - 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)) + Float64(Float64(1.0 - cos(Float64(phi1 - phi2))) / 2.0))), sqrt(Float64(1.0 - (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)) + ((1.0 - cos((phi1 - phi2))) / 2.0))), sqrt((1.0 - (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[(N[(1.0 - N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\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) + \frac{1 - \cos \left(\phi_1 - \phi_2\right)}{2}}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 65.9%
associate-*l*65.9%
Simplified65.9%
Taylor expanded in phi1 around 0 52.5%
+-commutative52.5%
associate--r+52.5%
unpow252.5%
1-sub-sin52.5%
unpow252.5%
sub-neg52.5%
mul-1-neg52.5%
distribute-lft-in52.5%
metadata-eval52.5%
associate-*r*52.5%
associate-*r*52.5%
metadata-eval52.5%
distribute-lft-in52.5%
+-commutative52.5%
Simplified52.5%
Taylor expanded in phi2 around 0 40.0%
unpow240.0%
sin-mult36.4%
div-inv36.4%
metadata-eval36.4%
div-inv36.4%
metadata-eval36.4%
div-inv36.4%
metadata-eval36.4%
div-inv36.4%
metadata-eval36.4%
Applied egg-rr36.4%
+-inverses36.4%
cos-036.4%
distribute-lft-out36.4%
metadata-eval36.4%
*-rgt-identity36.4%
Simplified36.4%
Final simplification36.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (- 0.5 (/ (cos (- lambda1 lambda2)) 2.0)))
(/ (- 1.0 (cos (- phi1 phi2))) 2.0)))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5 - (cos((lambda1 - lambda2)) / 2.0))) + ((1.0 - cos((phi1 - phi2))) / 2.0))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5d0 - (cos((lambda1 - lambda2)) / 2.0d0))) + ((1.0d0 - cos((phi1 - phi2))) / 2.0d0))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (0.5 - (Math.cos((lambda1 - lambda2)) / 2.0))) + ((1.0 - Math.cos((phi1 - phi2))) / 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (0.5 - (math.cos((lambda1 - lambda2)) / 2.0))) + ((1.0 - math.cos((phi1 - phi2))) / 2.0))), math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) / 2.0))) + Float64(Float64(1.0 - cos(Float64(phi1 - phi2))) / 2.0))), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5 - (cos((lambda1 - lambda2)) / 2.0))) + ((1.0 - cos((phi1 - phi2))) / 2.0))), sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(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[(N[(1.0 - N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}\right) + \frac{1 - \cos \left(\phi_1 - \phi_2\right)}{2}}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
Initial program 65.9%
associate-*l*65.9%
Simplified65.9%
Taylor expanded in phi1 around 0 52.5%
+-commutative52.5%
associate--r+52.5%
unpow252.5%
1-sub-sin52.5%
unpow252.5%
sub-neg52.5%
mul-1-neg52.5%
distribute-lft-in52.5%
metadata-eval52.5%
associate-*r*52.5%
associate-*r*52.5%
metadata-eval52.5%
distribute-lft-in52.5%
+-commutative52.5%
Simplified52.5%
Taylor expanded in phi2 around 0 40.0%
unpow240.0%
sin-mult36.4%
div-inv36.4%
metadata-eval36.4%
div-inv36.4%
metadata-eval36.4%
div-inv36.4%
metadata-eval36.4%
div-inv36.4%
metadata-eval36.4%
Applied egg-rr36.4%
+-inverses36.4%
cos-036.4%
distribute-lft-out36.4%
metadata-eval36.4%
*-rgt-identity36.4%
Simplified36.4%
sin-mult33.7%
div-inv33.7%
metadata-eval33.7%
div-inv33.7%
metadata-eval33.7%
cos-sum33.6%
cos-233.7%
div-inv33.7%
metadata-eval33.7%
Applied egg-rr33.7%
div-sub33.7%
+-inverses33.7%
cos-033.7%
metadata-eval33.7%
*-commutative33.7%
associate-*r*33.7%
metadata-eval33.7%
Simplified33.7%
Final simplification33.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(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) {
return R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), 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
code = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), 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) {
return R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), 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): return R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), 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) return Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), 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) tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $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}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\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}
Initial program 65.9%
associate-*l*65.9%
Simplified65.9%
Taylor expanded in phi1 around 0 52.5%
+-commutative52.5%
associate--r+52.5%
unpow252.5%
1-sub-sin52.5%
unpow252.5%
sub-neg52.5%
mul-1-neg52.5%
distribute-lft-in52.5%
metadata-eval52.5%
associate-*r*52.5%
associate-*r*52.5%
metadata-eval52.5%
distribute-lft-in52.5%
+-commutative52.5%
Simplified52.5%
Taylor expanded in lambda1 around 0 40.4%
*-commutative40.4%
Simplified40.4%
Taylor expanded in lambda2 around 0 16.5%
Final simplification16.5%
herbie shell --seed 2024081
(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))))))))))