
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right) \cdot t_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_1}}{\sqrt{1 - t_1}}\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 22 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right) \cdot t_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_1}}{\sqrt{1 - t_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow
(fma
(sin (/ phi1 2.0))
(cos (/ phi2 2.0))
(* (sin (/ phi2 2.0)) (- (cos (/ phi1 2.0)))))
2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(t_2 (sqrt t_1))
(t_3
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))
(t_4
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))
t_3)))
(if (<= lambda2 -0.00016)
(* R (* 2.0 (atan2 (sqrt t_4) (sqrt (- 1.0 t_1)))))
(if (<= lambda2 0.0102)
(*
R
(*
2.0
(atan2
t_2
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0)))
t_3))))))
(* R (* 2.0 (atan2 t_2 (sqrt (- 1.0 t_4)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(fma(sin((phi1 / 2.0)), cos((phi2 / 2.0)), (sin((phi2 / 2.0)) * -cos((phi1 / 2.0)))), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0));
double t_2 = sqrt(t_1);
double t_3 = pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double t_4 = (cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))) + t_3;
double tmp;
if (lambda2 <= -0.00016) {
tmp = R * (2.0 * atan2(sqrt(t_4), sqrt((1.0 - t_1))));
} else if (lambda2 <= 0.0102) {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))) + t_3)))));
} else {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - t_4))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = 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) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0))) t_2 = sqrt(t_1) t_3 = Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_4 = Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))) + t_3) tmp = 0.0 if (lambda2 <= -0.00016) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_4), sqrt(Float64(1.0 - t_1))))); elseif (lambda2 <= 0.0102) tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))) + t_3)))))); else tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - t_4))))); 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[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] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[t$95$1], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 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$4 = N[(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] + t$95$3), $MachinePrecision]}, If[LessEqual[lambda2, -0.00016], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$4], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda2, 0.0102], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - t$95$4), $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(\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_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right)\\
t_2 := \sqrt{t_1}\\
t_3 := {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_4 := \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right) + t_3\\
\mathbf{if}\;\lambda_2 \leq -0.00016:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_4}}{\sqrt{1 - t_1}}\right)\\
\mathbf{elif}\;\lambda_2 \leq 0.0102:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_2}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}\right) + t_3\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_2}{\sqrt{1 - t_4}}\right)\\
\end{array}
\end{array}
if lambda2 < -1.60000000000000013e-4Initial program 51.3%
div-sub51.3%
sin-diff52.4%
Applied egg-rr52.4%
fma-neg52.4%
distribute-rgt-neg-in52.4%
Simplified52.4%
div-sub51.3%
sin-diff52.4%
Applied egg-rr65.6%
fma-neg52.4%
distribute-rgt-neg-in52.4%
Simplified65.6%
Taylor expanded in lambda1 around 0 65.8%
if -1.60000000000000013e-4 < lambda2 < 0.010200000000000001Initial program 76.1%
div-sub76.1%
sin-diff77.1%
Applied egg-rr77.1%
fma-neg77.1%
distribute-rgt-neg-in77.1%
Simplified77.1%
div-sub76.1%
sin-diff77.1%
Applied egg-rr97.3%
fma-neg77.1%
distribute-rgt-neg-in77.1%
Simplified97.3%
add-cbrt-cube97.2%
pow397.2%
pow-pow97.2%
Applied egg-rr97.2%
Simplified97.2%
Taylor expanded in lambda2 around 0 97.3%
if 0.010200000000000001 < lambda2 Initial program 47.8%
div-sub47.8%
sin-diff50.6%
Applied egg-rr50.6%
fma-neg50.6%
distribute-rgt-neg-in50.6%
Simplified50.6%
div-sub47.8%
sin-diff50.6%
Applied egg-rr57.0%
fma-neg50.6%
distribute-rgt-neg-in50.6%
Simplified57.0%
add-cbrt-cube56.9%
pow356.9%
pow-pow56.9%
Applied egg-rr56.9%
Simplified56.9%
Taylor expanded in lambda1 around 0 56.9%
Final simplification79.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ phi1 2.0)))
(t_1 (cos (/ phi2 2.0)))
(t_2 (sin (/ phi2 2.0)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* t_3 (* (* (cos phi1) (cos phi2)) t_3)))
(t_5 (* t_3 (* (cos phi2) (* (cos phi1) t_3))))
(t_6 (cos (/ phi1 2.0))))
(if (<= (+ t_4 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)) 4e-17)
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_0 t_1 (* t_2 (- t_6))) 2.0) t_4))
(sqrt
(-
1.0
(+
(* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi1 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (- 0.5 (/ (cos (- phi1 phi2)) 2.0)) t_5))
(sqrt (- 1.0 (+ (pow (- (* t_0 t_1) (* t_6 t_2)) 2.0) t_5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 / 2.0));
double t_1 = cos((phi2 / 2.0));
double t_2 = sin((phi2 / 2.0));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = t_3 * ((cos(phi1) * cos(phi2)) * t_3);
double t_5 = t_3 * (cos(phi2) * (cos(phi1) * t_3));
double t_6 = cos((phi1 / 2.0));
double tmp;
if ((t_4 + pow(sin(((phi1 - phi2) / 2.0)), 2.0)) <= 4e-17) {
tmp = R * (2.0 * atan2(sqrt((pow(fma(t_0, t_1, (t_2 * -t_6)), 2.0) + t_4)), sqrt((1.0 - ((cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((0.5 - (cos((phi1 - phi2)) / 2.0)) + t_5)), sqrt((1.0 - (pow(((t_0 * t_1) - (t_6 * t_2)), 2.0) + t_5)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 / 2.0)) t_1 = cos(Float64(phi2 / 2.0)) t_2 = sin(Float64(phi2 / 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 = Float64(t_3 * Float64(cos(phi2) * Float64(cos(phi1) * t_3))) t_6 = cos(Float64(phi1 / 2.0)) tmp = 0.0 if (Float64(t_4 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) <= 4e-17) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_0, t_1, Float64(t_2 * Float64(-t_6))) ^ 2.0) + t_4)), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)) + t_5)), sqrt(Float64(1.0 - Float64((Float64(Float64(t_0 * t_1) - Float64(t_6 * t_2)) ^ 2.0) + t_5)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi2 / 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[(t$95$3 * N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(t$95$4 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision], 4e-17], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$0 * t$95$1 + N[(t$95$2 * (-t$95$6)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision] + t$95$5), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[(t$95$0 * t$95$1), $MachinePrecision] - N[(t$95$6 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\phi_1}{2}\right)\\
t_1 := \cos \left(\frac{\phi_2}{2}\right)\\
t_2 := \sin \left(\frac{\phi_2}{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 := t_3 \cdot \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot t_3\right)\right)\\
t_6 := \cos \left(\frac{\phi_1}{2}\right)\\
\mathbf{if}\;t_4 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} \leq 4 \cdot 10^{-17}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t_0, t_1, t_2 \cdot \left(-t_6\right)\right)\right)}^{2} + t_4}}{\sqrt{1 - \left(\cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right) + t_5}}{\sqrt{1 - \left({\left(t_0 \cdot t_1 - t_6 \cdot t_2\right)}^{2} + t_5\right)}}\right)\\
\end{array}
\end{array}
if (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) 2)) 2) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)))) < 4.00000000000000029e-17Initial program 68.3%
div-sub68.3%
sin-diff68.3%
Applied egg-rr68.3%
fma-neg68.3%
distribute-rgt-neg-in68.3%
Simplified68.3%
div-sub68.3%
sin-diff68.3%
Applied egg-rr88.9%
fma-neg68.3%
distribute-rgt-neg-in68.3%
Simplified88.9%
Taylor expanded in phi2 around 0 74.4%
if 4.00000000000000029e-17 < (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) 2)) 2) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)))) Initial program 62.7%
Simplified62.7%
unpow262.7%
sin-mult62.7%
div-inv62.7%
metadata-eval62.7%
div-inv62.7%
metadata-eval62.7%
div-inv62.7%
metadata-eval62.7%
div-inv62.7%
metadata-eval62.7%
Applied egg-rr62.6%
div-sub62.7%
+-inverses62.7%
cos-062.7%
metadata-eval62.7%
distribute-lft-out62.7%
metadata-eval62.7%
*-rgt-identity62.7%
Simplified62.6%
div-sub62.7%
sin-diff64.3%
Applied egg-rr64.3%
Final simplification65.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ phi1 2.0)))
(t_1 (cos (/ phi2 2.0)))
(t_2 (sin (/ phi2 2.0)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* t_3 (* (* (cos phi1) (cos phi2)) t_3)))
(t_5 (* t_3 (* (cos phi2) (* (cos phi1) t_3))))
(t_6 (cos (/ phi1 2.0))))
(if (<= (+ t_4 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)) 0.012)
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_0 t_1 (* t_2 (- t_6))) 2.0) t_4))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi2 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (- 0.5 (/ (cos (- phi1 phi2)) 2.0)) t_5))
(sqrt (- 1.0 (+ (pow (- (* t_0 t_1) (* t_6 t_2)) 2.0) t_5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 / 2.0));
double t_1 = cos((phi2 / 2.0));
double t_2 = sin((phi2 / 2.0));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = t_3 * ((cos(phi1) * cos(phi2)) * t_3);
double t_5 = t_3 * (cos(phi2) * (cos(phi1) * t_3));
double t_6 = cos((phi1 / 2.0));
double tmp;
if ((t_4 + pow(sin(((phi1 - phi2) / 2.0)), 2.0)) <= 0.012) {
tmp = R * (2.0 * atan2(sqrt((pow(fma(t_0, t_1, (t_2 * -t_6)), 2.0) + t_4)), sqrt((1.0 - ((cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi2 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((0.5 - (cos((phi1 - phi2)) / 2.0)) + t_5)), sqrt((1.0 - (pow(((t_0 * t_1) - (t_6 * t_2)), 2.0) + t_5)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 / 2.0)) t_1 = cos(Float64(phi2 / 2.0)) t_2 = sin(Float64(phi2 / 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 = Float64(t_3 * Float64(cos(phi2) * Float64(cos(phi1) * t_3))) t_6 = cos(Float64(phi1 / 2.0)) tmp = 0.0 if (Float64(t_4 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) <= 0.012) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_0, t_1, Float64(t_2 * Float64(-t_6))) ^ 2.0) + t_4)), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi2 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)) + t_5)), sqrt(Float64(1.0 - Float64((Float64(Float64(t_0 * t_1) - Float64(t_6 * t_2)) ^ 2.0) + t_5)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi2 / 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[(t$95$3 * N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(t$95$4 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision], 0.012], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$0 * t$95$1 + N[(t$95$2 * (-t$95$6)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision] + t$95$5), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[(t$95$0 * t$95$1), $MachinePrecision] - N[(t$95$6 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\phi_1}{2}\right)\\
t_1 := \cos \left(\frac{\phi_2}{2}\right)\\
t_2 := \sin \left(\frac{\phi_2}{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 := t_3 \cdot \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot t_3\right)\right)\\
t_6 := \cos \left(\frac{\phi_1}{2}\right)\\
\mathbf{if}\;t_4 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} \leq 0.012:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t_0, t_1, t_2 \cdot \left(-t_6\right)\right)\right)}^{2} + t_4}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right) + t_5}}{\sqrt{1 - \left({\left(t_0 \cdot t_1 - t_6 \cdot t_2\right)}^{2} + t_5\right)}}\right)\\
\end{array}
\end{array}
if (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) 2)) 2) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)))) < 0.012Initial program 65.1%
div-sub65.1%
sin-diff65.1%
Applied egg-rr65.1%
fma-neg65.1%
distribute-rgt-neg-in65.1%
Simplified65.1%
div-sub65.1%
sin-diff65.1%
Applied egg-rr88.7%
fma-neg65.1%
distribute-rgt-neg-in65.1%
Simplified88.7%
Taylor expanded in phi1 around 0 71.1%
if 0.012 < (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) 2)) 2) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)))) Initial program 63.0%
Simplified63.0%
unpow263.0%
sin-mult63.0%
div-inv63.0%
metadata-eval63.0%
div-inv63.0%
metadata-eval63.0%
div-inv63.0%
metadata-eval63.0%
div-inv63.0%
metadata-eval63.0%
Applied egg-rr63.0%
div-sub63.0%
+-inverses63.0%
cos-063.0%
metadata-eval63.0%
distribute-lft-out63.0%
metadata-eval63.0%
*-rgt-identity63.0%
Simplified63.0%
div-sub63.0%
sin-diff64.7%
Applied egg-rr64.7%
Final simplification65.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (cos phi2) (* (cos phi1) t_0))))
(t_2 (* t_0 (* (* (cos phi1) (cos phi2)) t_0)))
(t_3 (+ t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(if (<= t_3 0.01)
(*
R
(*
2.0
(atan2
(sqrt
(+
t_2
(pow
(+ (sin (* phi2 -0.5)) (* 0.5 (* phi1 (cos (* phi2 -0.5)))))
2.0)))
(sqrt (- 1.0 t_3)))))
(*
R
(*
2.0
(atan2
(sqrt (+ (- 0.5 (/ (cos (- phi1 phi2)) 2.0)) t_1))
(sqrt
(-
1.0
(+
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)
t_1)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * (cos(phi2) * (cos(phi1) * t_0));
double t_2 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
double t_3 = t_2 + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (t_3 <= 0.01) {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow((sin((phi2 * -0.5)) + (0.5 * (phi1 * cos((phi2 * -0.5))))), 2.0))), sqrt((1.0 - t_3))));
} else {
tmp = R * (2.0 * atan2(sqrt(((0.5 - (cos((phi1 - phi2)) / 2.0)) + t_1)), sqrt((1.0 - (pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0) + t_1)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * (cos(phi2) * (cos(phi1) * t_0))
t_2 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
t_3 = t_2 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)
if (t_3 <= 0.01d0) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + ((sin((phi2 * (-0.5d0))) + (0.5d0 * (phi1 * cos((phi2 * (-0.5d0)))))) ** 2.0d0))), sqrt((1.0d0 - t_3))))
else
tmp = r * (2.0d0 * atan2(sqrt(((0.5d0 - (cos((phi1 - phi2)) / 2.0d0)) + t_1)), sqrt((1.0d0 - ((((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0) + t_1)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * (Math.cos(phi2) * (Math.cos(phi1) * t_0));
double t_2 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
double t_3 = t_2 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (t_3 <= 0.01) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow((Math.sin((phi2 * -0.5)) + (0.5 * (phi1 * Math.cos((phi2 * -0.5))))), 2.0))), Math.sqrt((1.0 - t_3))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((0.5 - (Math.cos((phi1 - phi2)) / 2.0)) + t_1)), Math.sqrt((1.0 - (Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0) + t_1)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * (math.cos(phi2) * (math.cos(phi1) * t_0)) t_2 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) t_3 = t_2 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) tmp = 0 if t_3 <= 0.01: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow((math.sin((phi2 * -0.5)) + (0.5 * (phi1 * math.cos((phi2 * -0.5))))), 2.0))), math.sqrt((1.0 - t_3)))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((0.5 - (math.cos((phi1 - phi2)) / 2.0)) + t_1)), math.sqrt((1.0 - (math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) + t_1))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(cos(phi2) * Float64(cos(phi1) * t_0))) t_2 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) t_3 = Float64(t_2 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) tmp = 0.0 if (t_3 <= 0.01) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (Float64(sin(Float64(phi2 * -0.5)) + Float64(0.5 * Float64(phi1 * cos(Float64(phi2 * -0.5))))) ^ 2.0))), sqrt(Float64(1.0 - t_3))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)) + t_1)), sqrt(Float64(1.0 - 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)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * (cos(phi2) * (cos(phi1) * t_0)); t_2 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); t_3 = t_2 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0); tmp = 0.0; if (t_3 <= 0.01) tmp = R * (2.0 * atan2(sqrt((t_2 + ((sin((phi2 * -0.5)) + (0.5 * (phi1 * cos((phi2 * -0.5))))) ^ 2.0))), sqrt((1.0 - t_3)))); else tmp = R * (2.0 * atan2(sqrt(((0.5 - (cos((phi1 - phi2)) / 2.0)) + t_1)), sqrt((1.0 - ((((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0) + t_1))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$3, 0.01], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] + N[(0.5 * N[(phi1 * N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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]], $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(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot t_0\right)\right)\\
t_2 := t_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right)\\
t_3 := t_2 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;t_3 \leq 0.01:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_2 + {\left(\sin \left(\phi_2 \cdot -0.5\right) + 0.5 \cdot \left(\phi_1 \cdot \cos \left(\phi_2 \cdot -0.5\right)\right)\right)}^{2}}}{\sqrt{1 - t_3}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right) + t_1}}{\sqrt{1 - \left({\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\right)}}\right)\\
\end{array}
\end{array}
if (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) 2)) 2) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)))) < 0.0100000000000000002Initial program 66.4%
Taylor expanded in phi1 around 0 70.5%
if 0.0100000000000000002 < (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) 2)) 2) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)))) Initial program 62.8%
Simplified62.8%
unpow262.8%
sin-mult62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
Applied egg-rr62.8%
div-sub62.8%
+-inverses62.8%
cos-062.8%
metadata-eval62.8%
distribute-lft-out62.8%
metadata-eval62.8%
*-rgt-identity62.8%
Simplified62.8%
div-sub62.8%
sin-diff64.5%
Applied egg-rr64.5%
Final simplification65.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow
(fma
(sin (/ phi1 2.0))
(cos (/ phi2 2.0))
(* (sin (/ phi2 2.0)) (- (cos (/ phi1 2.0)))))
2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) 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(fma(sin((phi1 / 2.0)), cos((phi2 / 2.0)), (sin((phi2 / 2.0)) * -cos((phi1 / 2.0)))), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0));
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = 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) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0))) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[(N[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] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\left(\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_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}}{\sqrt{1 - t_1}}\right)
\end{array}
\end{array}
Initial program 63.3%
div-sub63.3%
sin-diff64.7%
Applied egg-rr64.7%
fma-neg64.7%
distribute-rgt-neg-in64.7%
Simplified64.7%
div-sub63.3%
sin-diff64.7%
Applied egg-rr79.8%
fma-neg64.7%
distribute-rgt-neg-in64.7%
Simplified79.9%
Final simplification79.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (/ phi1 2.0)))
(t_1 (sin (/ phi2 2.0)))
(t_2 (sin (/ phi1 2.0)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* t_3 (* (* (cos phi1) (cos phi2)) t_3)))
(t_5 (cos (/ phi2 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_4 (pow (- (* t_2 t_5) (* t_0 t_1)) 2.0)))
(sqrt (- 1.0 (+ (pow (fma t_2 t_5 (* t_1 (- t_0))) 2.0) t_4))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 / 2.0));
double t_1 = sin((phi2 / 2.0));
double t_2 = sin((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 = cos((phi2 / 2.0));
return R * (2.0 * atan2(sqrt((t_4 + pow(((t_2 * t_5) - (t_0 * t_1)), 2.0))), sqrt((1.0 - (pow(fma(t_2, t_5, (t_1 * -t_0)), 2.0) + t_4)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 / 2.0)) t_1 = sin(Float64(phi2 / 2.0)) t_2 = sin(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 = cos(Float64(phi2 / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + (Float64(Float64(t_2 * t_5) - Float64(t_0 * t_1)) ^ 2.0))), sqrt(Float64(1.0 - Float64((fma(t_2, t_5, Float64(t_1 * Float64(-t_0))) ^ 2.0) + t_4)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[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[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + N[Power[N[(N[(t$95$2 * t$95$5), $MachinePrecision] - N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(t$95$2 * t$95$5 + N[(t$95$1 * (-t$95$0)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\frac{\phi_1}{2}\right)\\
t_1 := \sin \left(\frac{\phi_2}{2}\right)\\
t_2 := \sin \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 := \cos \left(\frac{\phi_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_4 + {\left(t_2 \cdot t_5 - t_0 \cdot t_1\right)}^{2}}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(t_2, t_5, t_1 \cdot \left(-t_0\right)\right)\right)}^{2} + t_4\right)}}\right)
\end{array}
\end{array}
Initial program 63.3%
div-sub63.3%
sin-diff64.7%
Applied egg-rr64.7%
fma-neg64.7%
distribute-rgt-neg-in64.7%
Simplified64.7%
div-sub63.3%
sin-diff64.7%
Applied egg-rr79.8%
Final simplification79.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(pow
(fma
(sin (/ phi1 2.0))
(cos (/ phi2 2.0))
(* (sin (/ phi2 2.0)) (- (cos (/ phi1 2.0)))))
2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0)))))
(t_2
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(if (or (<= lambda2 -0.00016) (not (<= lambda2 0.0102)))
(*
R
(*
2.0
(atan2
t_1
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))
t_2))))))
(*
R
(*
2.0
(atan2
t_1
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0)))
t_2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sqrt((pow(fma(sin((phi1 / 2.0)), cos((phi2 / 2.0)), (sin((phi2 / 2.0)) * -cos((phi1 / 2.0)))), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0))));
double t_2 = pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double tmp;
if ((lambda2 <= -0.00016) || !(lambda2 <= 0.0102)) {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))) + t_2)))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))) + t_2)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = 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) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))) t_2 = Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 tmp = 0.0 if ((lambda2 <= -0.00016) || !(lambda2 <= 0.0102)) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))) + t_2)))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))) + t_2)))))); 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[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] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 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[Or[LessEqual[lambda2, -0.00016], N[Not[LessEqual[lambda2, 0.0102]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[(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] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[(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] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{{\left(\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_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right)}\\
t_2 := {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \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_2 \leq -0.00016 \lor \neg \left(\lambda_2 \leq 0.0102\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right) + t_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}\right) + t_2\right)}}\right)\\
\end{array}
\end{array}
if lambda2 < -1.60000000000000013e-4 or 0.010200000000000001 < lambda2 Initial program 49.6%
div-sub49.6%
sin-diff51.5%
Applied egg-rr51.5%
fma-neg51.5%
distribute-rgt-neg-in51.5%
Simplified51.5%
div-sub49.6%
sin-diff51.5%
Applied egg-rr61.3%
fma-neg51.5%
distribute-rgt-neg-in51.5%
Simplified61.3%
add-cbrt-cube61.2%
pow361.2%
pow-pow61.2%
Applied egg-rr61.2%
Simplified61.2%
Taylor expanded in lambda1 around 0 61.3%
if -1.60000000000000013e-4 < lambda2 < 0.010200000000000001Initial program 76.1%
div-sub76.1%
sin-diff77.1%
Applied egg-rr77.1%
fma-neg77.1%
distribute-rgt-neg-in77.1%
Simplified77.1%
div-sub76.1%
sin-diff77.1%
Applied egg-rr97.3%
fma-neg77.1%
distribute-rgt-neg-in77.1%
Simplified97.3%
add-cbrt-cube97.2%
pow397.2%
pow-pow97.2%
Applied egg-rr97.2%
Simplified97.2%
Taylor expanded in lambda2 around 0 97.3%
Final simplification79.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (cos (/ phi2 2.0)))
(t_2 (sin (/ phi2 2.0)))
(t_3 (* t_0 (* (cos phi2) (* (cos phi1) t_0))))
(t_4 (sin (/ phi1 2.0)))
(t_5 (cos (/ phi1 2.0)))
(t_6 (+ (pow (- (* t_4 t_1) (* t_5 t_2)) 2.0) t_3))
(t_7 (* (cos phi1) (cos phi2))))
(if (<= lambda1 -1.3e-5)
(*
R
(*
2.0
(atan2
(sqrt (+ (- 0.5 (/ (cos (- phi1 phi2)) 2.0)) t_3))
(sqrt (- 1.0 t_6)))))
(if (<= lambda1 8e-6)
(*
R
(*
2.0
(atan2
(sqrt
(+ (pow (fma t_4 t_1 (* t_2 (- t_5))) 2.0) (* t_0 (* t_7 t_0))))
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt t_6)
(sqrt
(exp
(log1p
(-
(fma
t_7
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos((phi2 / 2.0));
double t_2 = sin((phi2 / 2.0));
double t_3 = t_0 * (cos(phi2) * (cos(phi1) * t_0));
double t_4 = sin((phi1 / 2.0));
double t_5 = cos((phi1 / 2.0));
double t_6 = pow(((t_4 * t_1) - (t_5 * t_2)), 2.0) + t_3;
double t_7 = cos(phi1) * cos(phi2);
double tmp;
if (lambda1 <= -1.3e-5) {
tmp = R * (2.0 * atan2(sqrt(((0.5 - (cos((phi1 - phi2)) / 2.0)) + t_3)), sqrt((1.0 - t_6))));
} else if (lambda1 <= 8e-6) {
tmp = R * (2.0 * atan2(sqrt((pow(fma(t_4, t_1, (t_2 * -t_5)), 2.0) + (t_0 * (t_7 * t_0)))), sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))) + pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_6), sqrt(exp(log1p(-fma(t_7, (0.5 - (0.5 * cos((lambda1 - lambda2)))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = cos(Float64(phi2 / 2.0)) t_2 = sin(Float64(phi2 / 2.0)) t_3 = Float64(t_0 * Float64(cos(phi2) * Float64(cos(phi1) * t_0))) t_4 = sin(Float64(phi1 / 2.0)) t_5 = cos(Float64(phi1 / 2.0)) t_6 = Float64((Float64(Float64(t_4 * t_1) - Float64(t_5 * t_2)) ^ 2.0) + t_3) t_7 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if (lambda1 <= -1.3e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)) + t_3)), sqrt(Float64(1.0 - t_6))))); elseif (lambda1 <= 8e-6) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_4, t_1, Float64(t_2 * Float64(-t_5))) ^ 2.0) + Float64(t_0 * Float64(t_7 * t_0)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))) + (Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_6), sqrt(exp(log1p(Float64(-fma(t_7, Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[(N[Power[N[(N[(t$95$4 * t$95$1), $MachinePrecision] - N[(t$95$5 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision]}, Block[{t$95$7 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[lambda1, -1.3e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$6), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 8e-6], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$4 * t$95$1 + N[(t$95$2 * (-t$95$5)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$7 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(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] + N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 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]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$6], $MachinePrecision] / N[Sqrt[N[Exp[N[Log[1 + (-N[(t$95$7 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision])], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \left(\frac{\phi_2}{2}\right)\\
t_2 := \sin \left(\frac{\phi_2}{2}\right)\\
t_3 := t_0 \cdot \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot t_0\right)\right)\\
t_4 := \sin \left(\frac{\phi_1}{2}\right)\\
t_5 := \cos \left(\frac{\phi_1}{2}\right)\\
t_6 := {\left(t_4 \cdot t_1 - t_5 \cdot t_2\right)}^{2} + t_3\\
t_7 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\lambda_1 \leq -1.3 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right) + t_3}}{\sqrt{1 - t_6}}\right)\\
\mathbf{elif}\;\lambda_1 \leq 8 \cdot 10^{-6}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t_4, t_1, t_2 \cdot \left(-t_5\right)\right)\right)}^{2} + t_0 \cdot \left(t_7 \cdot t_0\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right) + {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_6}}{\sqrt{e^{\mathsf{log1p}\left(-\mathsf{fma}\left(t_7, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right)}}}\right)\\
\end{array}
\end{array}
if lambda1 < -1.29999999999999992e-5Initial program 44.3%
Simplified44.3%
unpow244.3%
sin-mult44.3%
div-inv44.3%
metadata-eval44.3%
div-inv44.3%
metadata-eval44.3%
div-inv44.3%
metadata-eval44.3%
div-inv44.3%
metadata-eval44.3%
Applied egg-rr44.4%
div-sub44.3%
+-inverses44.3%
cos-044.3%
metadata-eval44.3%
distribute-lft-out44.3%
metadata-eval44.3%
*-rgt-identity44.3%
Simplified44.4%
div-sub44.3%
sin-diff47.1%
Applied egg-rr47.1%
if -1.29999999999999992e-5 < lambda1 < 7.99999999999999964e-6Initial program 78.3%
div-sub78.3%
sin-diff79.4%
Applied egg-rr79.4%
fma-neg79.4%
distribute-rgt-neg-in79.4%
Simplified79.4%
div-sub78.3%
sin-diff79.4%
Applied egg-rr98.2%
fma-neg79.4%
distribute-rgt-neg-in79.4%
Simplified98.2%
add-cbrt-cube98.1%
pow398.1%
pow-pow98.1%
Applied egg-rr98.1%
Simplified98.1%
Taylor expanded in lambda1 around 0 98.3%
if 7.99999999999999964e-6 < lambda1 Initial program 52.3%
Simplified52.3%
Applied egg-rr52.4%
div-sub52.3%
sin-diff53.0%
Applied egg-rr53.2%
Final simplification74.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* (cos phi2) (* (cos phi1) t_0)))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(exp
(log1p
(-
(fma
(* (cos phi1) (cos phi2))
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 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(((t_0 * (cos(phi2) * (cos(phi1) * t_0))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(exp(log1p(-fma((cos(phi1) * cos(phi2)), (0.5 - (0.5 * cos((lambda1 - lambda2)))), pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 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(Float64(t_0 * Float64(cos(phi2) * Float64(cos(phi1) * t_0))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(exp(log1p(Float64(-fma(Float64(cos(phi1) * cos(phi2)), Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), (Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 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[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Exp[N[Log[1 + (-N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 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]], $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{t_0 \cdot \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot t_0\right)\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{e^{\mathsf{log1p}\left(-\mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)\right)}}}\right)
\end{array}
\end{array}
Initial program 63.3%
Simplified63.3%
Applied egg-rr63.3%
metadata-eval63.3%
div-inv63.3%
div-sub63.3%
sin-diff64.7%
div-inv64.7%
metadata-eval64.7%
div-inv64.7%
metadata-eval64.7%
div-inv64.7%
metadata-eval64.7%
div-inv64.7%
metadata-eval64.7%
Applied egg-rr64.7%
Final simplification64.7%
(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
(+
(pow
(fma
(sin (/ phi1 2.0))
(cos (/ phi2 2.0))
(* (sin (/ phi2 2.0)) (- (cos (/ phi1 2.0)))))
2.0)
t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (pow(fma(sin((phi1 / 2.0)), cos((phi2 / 2.0)), (sin((phi2 / 2.0)) * -cos((phi1 / 2.0)))), 2.0) + t_1)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - 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)))))) 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[(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]], $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({\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\right)}}\right)
\end{array}
\end{array}
Initial program 63.3%
div-sub63.3%
sin-diff64.7%
Applied egg-rr64.7%
fma-neg64.7%
distribute-rgt-neg-in64.7%
Simplified64.7%
Final simplification64.7%
(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 63.3%
div-sub63.3%
sin-diff64.7%
Applied egg-rr64.7%
Final simplification64.7%
(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)))
(if (or (<= t_0 -0.1) (not (<= t_0 1e-16)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* (* (cos phi1) (cos phi2)) t_0)) t_1))
(sqrt
(-
1.0
(+
(* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi1 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (fma (cos phi1) (* (cos phi2) (* t_0 t_0)) t_1))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi2 phi1))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((t_0 <= -0.1) || !(t_0 <= 1e-16)) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + t_1)), sqrt((1.0 - ((cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi1), (cos(phi2) * (t_0 * t_0)), t_1)), sqrt((1.0 - pow(sin((0.5 * (phi2 - phi1))), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if ((t_0 <= -0.1) || !(t_0 <= 1e-16)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + t_1)), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), Float64(cos(phi2) * Float64(t_0 * t_0)), t_1)), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi2 - phi1))) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[t$95$0, -0.1], N[Not[LessEqual[t$95$0, 1e-16]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[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] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi2 - phi1), $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)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;t_0 \leq -0.1 \lor \neg \left(t_0 \leq 10^{-16}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right) + t_1}}{\sqrt{1 - \left(\cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(t_0 \cdot t_0\right), t_1\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) < -0.10000000000000001 or 9.9999999999999998e-17 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) Initial program 58.2%
div-sub58.2%
sin-diff59.9%
Applied egg-rr59.9%
fma-neg59.9%
distribute-rgt-neg-in59.9%
Simplified59.9%
Taylor expanded in phi2 around 0 47.6%
if -0.10000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) < 9.9999999999999998e-17Initial program 76.2%
Simplified76.2%
Taylor expanded in lambda2 around 0 74.4%
Taylor expanded in lambda1 around 0 71.6%
Final simplification54.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* t_1 t_1)))
(*
(atan2
(sqrt (fma t_0 t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (fma t_0 t_2 (- 0.5 (/ (cos (- phi1 phi2)) 2.0))))))
(* R 2.0))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * t_1;
return atan2(sqrt(fma(t_0, t_2, pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - fma(t_0, t_2, (0.5 - (cos((phi1 - phi2)) / 2.0)))))) * (R * 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)) t_2 = Float64(t_1 * t_1) return Float64(atan(sqrt(fma(t_0, t_2, (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_0, t_2, Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))))) * Float64(R * 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]}, Block[{t$95$2 = N[(t$95$1 * t$95$1), $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(t$95$0 * t$95$2 + 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$0 * t$95$2 + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t_1 \cdot t_1\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t_0, t_2, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t_0, t_2, 0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}} \cdot \left(R \cdot 2\right)
\end{array}
\end{array}
Initial program 63.3%
associate-*r*63.3%
*-commutative63.3%
Simplified63.3%
unpow263.3%
sin-mult63.3%
div-inv63.3%
metadata-eval63.3%
div-inv63.3%
metadata-eval63.3%
div-inv63.3%
metadata-eval63.3%
div-inv63.3%
metadata-eval63.3%
Applied egg-rr63.3%
div-sub63.3%
+-inverses63.3%
cos-063.3%
metadata-eval63.3%
distribute-lft-out63.3%
metadata-eval63.3%
*-rgt-identity63.3%
Simplified63.3%
Final simplification63.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* (cos phi2) (* (cos phi1) t_0)))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt(((t_0 * (cos(phi2) * (cos(phi1) * t_0))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), (0.5 - (0.5 * cos((lambda1 - lambda2)))), pow(sin((0.5 * (phi1 - phi2))), 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(t_0 * Float64(cos(phi2) * Float64(cos(phi1) * t_0))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_0 \cdot \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot t_0\right)\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.3%
Simplified63.3%
Applied egg-rr63.3%
Final simplification63.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (+ 1.0 (- (- (/ (cos (- phi1 phi2)) 2.0) 0.5) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = 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 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = 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 + (((cos((phi1 - phi2)) / 2.0d0) - 0.5d0) - t_1)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = 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 + (((Math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = 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 + (((math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(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(Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5) - t_1)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = 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 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(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[(N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision] - t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 + \left(\left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right) - t_1\right)}}\right)
\end{array}
\end{array}
Initial program 63.3%
unpow263.3%
sin-mult63.3%
div-inv63.3%
metadata-eval63.3%
div-inv63.3%
metadata-eval63.3%
div-inv63.3%
metadata-eval63.3%
div-inv63.3%
metadata-eval63.3%
Applied egg-rr63.3%
div-sub63.3%
+-inverses63.3%
cos-063.3%
metadata-eval63.3%
distribute-lft-out63.3%
metadata-eval63.3%
*-rgt-identity63.3%
Simplified63.3%
Final simplification63.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= phi1 -0.00145) (not (<= phi1 5.4e-9)))
(*
R
(*
2.0
(atan2
t_1
(sqrt (- 1.0 (+ (* (cos phi1) t_2) (pow (sin (* phi1 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
t_1
(sqrt
(- 1.0 (+ (* (cos phi2) t_2) (pow (sin (* phi2 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 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi1 <= -0.00145) || !(phi1 <= 5.4e-9)) {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - ((cos(phi1) * t_2) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - ((cos(phi2) * t_2) + pow(sin((phi2 * 0.5)), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)))
t_2 = sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
if ((phi1 <= (-0.00145d0)) .or. (.not. (phi1 <= 5.4d-9))) then
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - ((cos(phi1) * t_2) + (sin((phi1 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - ((cos(phi2) * t_2) + (sin((phi2 * 0.5d0)) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.sqrt(((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_2 = Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi1 <= -0.00145) || !(phi1 <= 5.4e-9)) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - ((Math.cos(phi1) * t_2) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - ((Math.cos(phi2) * t_2) + Math.pow(Math.sin((phi2 * 0.5)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt(((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))) t_2 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) tmp = 0 if (phi1 <= -0.00145) or not (phi1 <= 5.4e-9): tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - ((math.cos(phi1) * t_2) + math.pow(math.sin((phi1 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - ((math.cos(phi2) * t_2) + math.pow(math.sin((phi2 * 0.5)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((phi1 <= -0.00145) || !(phi1 <= 5.4e-9)) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_2) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_2) + (sin(Float64(phi2 * 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 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))); t_2 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; tmp = 0.0; if ((phi1 <= -0.00145) || ~((phi1 <= 5.4e-9))) tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - ((cos(phi1) * t_2) + (sin((phi1 * 0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - ((cos(phi2) * t_2) + (sin((phi2 * 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[Sqrt[N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -0.00145], N[Not[LessEqual[phi1, 5.4e-9]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{t_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -0.00145 \lor \neg \left(\phi_1 \leq 5.4 \cdot 10^{-9}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{1 - \left(\cos \phi_1 \cdot t_2 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{1 - \left(\cos \phi_2 \cdot t_2 + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -0.00145 or 5.4000000000000004e-9 < phi1 Initial program 48.0%
div-sub48.0%
sin-diff50.7%
Applied egg-rr50.7%
fma-neg50.7%
distribute-rgt-neg-in50.7%
Simplified50.7%
Taylor expanded in phi2 around 0 49.8%
if -0.00145 < phi1 < 5.4000000000000004e-9Initial program 79.5%
div-sub79.5%
sin-diff79.6%
Applied egg-rr79.6%
fma-neg79.6%
distribute-rgt-neg-in79.6%
Simplified79.6%
Taylor expanded in phi1 around 0 79.5%
Final simplification64.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= t_0 0.22)
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi1)
(* (cos phi2) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi2 phi1))) 2.0))))))
(*
R
(*
2.0
(atan2
(* (sin (* (- lambda1 lambda2) 0.5)) (sqrt (cos phi2)))
(sqrt
(-
1.0
(+
(*
(cos phi2)
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0))
(pow (sin (* phi2 -0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (t_0 <= 0.22) {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi1), (cos(phi2) * (t_0 * t_0)), pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi2 - phi1))), 2.0)))));
} else {
tmp = R * (2.0 * atan2((sin(((lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt((1.0 - ((cos(phi2) * pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0)) + pow(sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (t_0 <= 0.22) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), Float64(cos(phi2) * Float64(t_0 * t_0)), (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi2 - phi1))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(Float64(sin(Float64(Float64(lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$0, 0.22], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi2], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -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)\\
\mathbf{if}\;t_0 \leq 0.22:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(t_0 \cdot t_0\right), {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right) \cdot \sqrt{\cos \phi_2}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right)}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) < 0.220000000000000001Initial program 62.6%
Simplified62.6%
Taylor expanded in lambda2 around 0 50.0%
Taylor expanded in lambda1 around 0 41.3%
if 0.220000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) Initial program 65.1%
Taylor expanded in phi2 around 0 43.4%
Taylor expanded in phi1 around 0 31.1%
Taylor expanded in phi1 around 0 30.8%
*-commutative30.8%
metadata-eval30.8%
div-inv30.8%
div-sub30.8%
sin-diff31.4%
Applied egg-rr31.4%
Final simplification38.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (<= t_0 0.22)
(*
R
(*
2.0
(atan2
(sqrt (fma (cos phi1) (* (cos phi2) (* t_0 t_0)) t_1))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi2 phi1))) 2.0))))))
(*
R
(*
2.0
(atan2
(*
(sqrt (cos phi2))
(+ 1.0 (+ -1.0 (sin (* (- lambda1 lambda2) 0.5)))))
(sqrt (- 1.0 (+ (* t_0 (* (* (cos phi1) (cos phi2)) t_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);
double tmp;
if (t_0 <= 0.22) {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi1), (cos(phi2) * (t_0 * t_0)), t_1)), sqrt((1.0 - pow(sin((0.5 * (phi2 - phi1))), 2.0)))));
} else {
tmp = R * (2.0 * atan2((sqrt(cos(phi2)) * (1.0 + (-1.0 + sin(((lambda1 - lambda2) * 0.5))))), sqrt((1.0 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + t_1)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if (t_0 <= 0.22) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), Float64(cos(phi2) * Float64(t_0 * t_0)), t_1)), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi2 - phi1))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(Float64(sqrt(cos(phi2)) * Float64(1.0 + Float64(-1.0 + sin(Float64(Float64(lambda1 - lambda2) * 0.5))))), sqrt(Float64(1.0 - Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + t_1)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[t$95$0, 0.22], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(N[Sqrt[N[Cos[phi2], $MachinePrecision]], $MachinePrecision] * N[(1.0 + N[(-1.0 + N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - 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]], $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}\\
\mathbf{if}\;t_0 \leq 0.22:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(t_0 \cdot t_0\right), t_1\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2} \cdot \left(1 + \left(-1 + \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\right)\right)}{\sqrt{1 - \left(t_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right) + t_1\right)}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) < 0.220000000000000001Initial program 62.6%
Simplified62.6%
Taylor expanded in lambda2 around 0 50.0%
Taylor expanded in lambda1 around 0 41.3%
if 0.220000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) Initial program 65.1%
Taylor expanded in phi2 around 0 43.4%
Taylor expanded in phi1 around 0 31.1%
*-commutative31.1%
expm1-log1p-u31.2%
expm1-def31.1%
sub-neg31.1%
log1p-udef31.1%
rem-exp-log31.1%
metadata-eval31.1%
Applied egg-rr31.1%
associate-+l+31.2%
*-commutative31.2%
Simplified31.2%
Final simplification38.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(* (sin (* (- lambda1 lambda2) 0.5)) (sqrt (cos phi2)))
(sqrt
(-
1.0
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2((sin(((lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt((1.0 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin(((phi1 - 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
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2((sin(((lambda1 - lambda2) * 0.5d0)) * sqrt(cos(phi2))), sqrt((1.0d0 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - 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));
return R * (2.0 * Math.atan2((Math.sin(((lambda1 - lambda2) * 0.5)) * Math.sqrt(Math.cos(phi2))), Math.sqrt((1.0 - ((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2((math.sin(((lambda1 - lambda2) * 0.5)) * math.sqrt(math.cos(phi2))), math.sqrt((1.0 - ((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 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(Float64(sin(Float64(Float64(lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt(Float64(1.0 - Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2((sin(((lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt((1.0 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((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]}, N[(R * N[(2.0 * N[ArcTan[N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi2], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + 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)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right) \cdot \sqrt{\cos \phi_2}}{\sqrt{1 - \left(t_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.3%
Taylor expanded in phi2 around 0 40.7%
Taylor expanded in phi1 around 0 13.7%
Final simplification13.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(* (sin (* (- lambda1 lambda2) 0.5)) (sqrt (cos phi2)))
(sqrt
(-
1.0
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (* phi1 0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2((sin(((lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt((1.0 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin((phi1 * 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((sin(((lambda1 - lambda2) * 0.5d0)) * sqrt(cos(phi2))), sqrt((1.0d0 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin((phi1 * 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.sin(((lambda1 - lambda2) * 0.5)) * Math.sqrt(Math.cos(phi2))), Math.sqrt((1.0 - ((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(Math.sin((phi1 * 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.sin(((lambda1 - lambda2) * 0.5)) * math.sqrt(math.cos(phi2))), math.sqrt((1.0 - ((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(math.sin((phi1 * 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(Float64(sin(Float64(Float64(lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt(Float64(1.0 - Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(phi1 * 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((sin(((lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt((1.0 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin((phi1 * 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[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi2], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right) \cdot \sqrt{\cos \phi_2}}{\sqrt{1 - \left(t_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right) + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.3%
Taylor expanded in phi2 around 0 40.7%
Taylor expanded in phi1 around 0 13.7%
Taylor expanded in phi2 around 0 13.7%
Final simplification13.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(* (sin (* (- lambda1 lambda2) 0.5)) (sqrt (cos phi2)))
(sqrt
(+
1.0
(-
(* (cos phi2) (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5))
(pow (sin (* phi2 -0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2((sin(((lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt((1.0 + ((cos(phi2) * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)) - pow(sin((phi2 * -0.5)), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2((sin(((lambda1 - lambda2) * 0.5d0)) * sqrt(cos(phi2))), sqrt((1.0d0 + ((cos(phi2) * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0)) - (sin((phi2 * (-0.5d0))) ** 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(((lambda1 - lambda2) * 0.5)) * Math.sqrt(Math.cos(phi2))), Math.sqrt((1.0 + ((Math.cos(phi2) * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5)) - Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2((math.sin(((lambda1 - lambda2) * 0.5)) * math.sqrt(math.cos(phi2))), math.sqrt((1.0 + ((math.cos(phi2) * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5)) - math.pow(math.sin((phi2 * -0.5)), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(Float64(sin(Float64(Float64(lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt(Float64(1.0 + Float64(Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5)) - (sin(Float64(phi2 * -0.5)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2((sin(((lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt((1.0 + ((cos(phi2) * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)) - (sin((phi2 * -0.5)) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi2], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right) \cdot \sqrt{\cos \phi_2}}{\sqrt{1 + \left(\cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right) - {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)
\end{array}
Initial program 63.3%
Taylor expanded in phi2 around 0 40.7%
Taylor expanded in phi1 around 0 13.7%
Taylor expanded in phi1 around 0 13.6%
*-commutative13.6%
metadata-eval13.6%
div-inv13.6%
pow213.6%
sin-mult13.6%
Applied egg-rr13.6%
div-sub13.6%
+-inverses13.6%
cos-013.6%
metadata-eval13.6%
distribute-rgt-out13.6%
metadata-eval13.6%
*-rgt-identity13.6%
Simplified13.6%
Final simplification13.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5))))
(*
R
(* 2.0 (atan2 (* t_0 (sqrt (cos phi2))) (sqrt (- 1.0 (pow t_0 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
return R * (2.0 * atan2((t_0 * sqrt(cos(phi2))), sqrt((1.0 - pow(t_0, 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) * 0.5d0))
code = r * (2.0d0 * atan2((t_0 * sqrt(cos(phi2))), sqrt((1.0d0 - (t_0 ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) * 0.5));
return R * (2.0 * Math.atan2((t_0 * Math.sqrt(Math.cos(phi2))), Math.sqrt((1.0 - Math.pow(t_0, 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) * 0.5)) return R * (2.0 * math.atan2((t_0 * math.sqrt(math.cos(phi2))), math.sqrt((1.0 - math.pow(t_0, 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) return Float64(R * Float64(2.0 * atan(Float64(t_0 * sqrt(cos(phi2))), sqrt(Float64(1.0 - (t_0 ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)); tmp = R * (2.0 * atan2((t_0 * sqrt(cos(phi2))), sqrt((1.0 - (t_0 ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[(t$95$0 * N[Sqrt[N[Cos[phi2], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_0 \cdot \sqrt{\cos \phi_2}}{\sqrt{1 - {t_0}^{2}}}\right)
\end{array}
\end{array}
Initial program 63.3%
Taylor expanded in phi2 around 0 40.7%
Taylor expanded in phi1 around 0 13.7%
Taylor expanded in phi1 around 0 13.6%
Taylor expanded in phi2 around 0 13.6%
Final simplification13.6%
herbie shell --seed 2023331
(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))))))))))