
(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 (cos (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* t_1 t_1))
(t_3 (sin (* phi2 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi1)
(* (cos phi2) t_2)
(pow
(+
(fma (cos (* phi2 0.5)) (sin (* phi1 0.5)) (* t_0 (- t_3)))
(fma (- t_0) t_3 (* t_3 t_0)))
2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
t_2
(pow
(fma
(cos (/ phi1 2.0))
(sin (/ phi2 2.0))
(* (sin (/ phi1 2.0)) (- (cos (/ phi2 2.0)))))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * t_1;
double t_3 = sin((phi2 * 0.5));
return R * (2.0 * atan2(sqrt(fma(cos(phi1), (cos(phi2) * t_2), pow((fma(cos((phi2 * 0.5)), sin((phi1 * 0.5)), (t_0 * -t_3)) + fma(-t_0, t_3, (t_3 * t_0))), 2.0))), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), t_2, pow(fma(cos((phi1 / 2.0)), sin((phi2 / 2.0)), (sin((phi1 / 2.0)) * -cos((phi2 / 2.0)))), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(t_1 * t_1) t_3 = sin(Float64(phi2 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), Float64(cos(phi2) * t_2), (Float64(fma(cos(Float64(phi2 * 0.5)), sin(Float64(phi1 * 0.5)), Float64(t_0 * Float64(-t_3))) + fma(Float64(-t_0), t_3, Float64(t_3 * t_0))) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), t_2, (fma(cos(Float64(phi1 / 2.0)), sin(Float64(phi2 / 2.0)), Float64(sin(Float64(phi1 / 2.0)) * Float64(-cos(Float64(phi2 / 2.0))))) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $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]}, Block[{t$95$3 = N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] + N[(t$95$0 * (-t$95$3)), $MachinePrecision]), $MachinePrecision] + N[((-t$95$0) * t$95$3 + N[(t$95$3 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2 + N[Power[N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * (-N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision])), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot t\_1\\
t_3 := \sin \left(\phi_2 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot t\_2, {\left(\mathsf{fma}\left(\cos \left(\phi_2 \cdot 0.5\right), \sin \left(\phi_1 \cdot 0.5\right), t\_0 \cdot \left(-t\_3\right)\right) + \mathsf{fma}\left(-t\_0, t\_3, t\_3 \cdot t\_0\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_2, {\left(\mathsf{fma}\left(\cos \left(\frac{\phi_1}{2}\right), \sin \left(\frac{\phi_2}{2}\right), \sin \left(\frac{\phi_1}{2}\right) \cdot \left(-\cos \left(\frac{\phi_2}{2}\right)\right)\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.2%
Simplified63.2%
div-sub63.2%
sin-diff64.0%
Applied egg-rr64.0%
*-commutative64.0%
*-commutative64.0%
fmm-def64.0%
distribute-rgt-neg-in64.0%
Simplified64.0%
div-sub64.0%
sin-diff78.7%
Applied egg-rr78.7%
fmm-def78.8%
distribute-rgt-neg-in78.8%
Simplified78.8%
distribute-rgt-neg-out78.8%
fmm-def78.7%
*-un-lft-identity78.7%
prod-diff78.8%
Applied egg-rr78.8%
Simplified78.8%
Final simplification78.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (/ phi1 2.0)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* t_1 t_1))
(t_3 (sin (/ phi1 2.0)))
(t_4 (cos (/ phi2 2.0)))
(t_5 (sin (/ phi2 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi1)
(* (cos phi2) t_2)
(pow (fma t_3 t_4 (* t_5 (- t_0))) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
t_2
(pow (fma t_0 t_5 (* t_3 (- t_4))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 / 2.0));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * t_1;
double t_3 = sin((phi1 / 2.0));
double t_4 = cos((phi2 / 2.0));
double t_5 = sin((phi2 / 2.0));
return R * (2.0 * atan2(sqrt(fma(cos(phi1), (cos(phi2) * t_2), pow(fma(t_3, t_4, (t_5 * -t_0)), 2.0))), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), t_2, pow(fma(t_0, t_5, (t_3 * -t_4)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 / 2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(t_1 * t_1) t_3 = sin(Float64(phi1 / 2.0)) t_4 = cos(Float64(phi2 / 2.0)) t_5 = sin(Float64(phi2 / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), Float64(cos(phi2) * t_2), (fma(t_3, t_4, Float64(t_5 * Float64(-t_0))) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), t_2, (fma(t_0, t_5, Float64(t_3 * Float64(-t_4))) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[(t$95$3 * t$95$4 + N[(t$95$5 * (-t$95$0)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2 + N[Power[N[(t$95$0 * t$95$5 + N[(t$95$3 * (-t$95$4)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\frac{\phi_1}{2}\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot t\_1\\
t_3 := \sin \left(\frac{\phi_1}{2}\right)\\
t_4 := \cos \left(\frac{\phi_2}{2}\right)\\
t_5 := \sin \left(\frac{\phi_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot t\_2, {\left(\mathsf{fma}\left(t\_3, t\_4, t\_5 \cdot \left(-t\_0\right)\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_2, {\left(\mathsf{fma}\left(t\_0, t\_5, t\_3 \cdot \left(-t\_4\right)\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.2%
Simplified63.2%
div-sub63.2%
sin-diff64.0%
Applied egg-rr64.0%
*-commutative64.0%
*-commutative64.0%
fmm-def64.0%
distribute-rgt-neg-in64.0%
Simplified64.0%
div-sub64.0%
sin-diff78.7%
Applied egg-rr78.7%
fmm-def78.8%
distribute-rgt-neg-in78.8%
Simplified78.8%
Final simplification78.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ phi2 2.0)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* t_1 t_1))
(t_3 (sin (/ phi1 2.0)))
(t_4 (cos (/ phi2 2.0)))
(t_5 (cos (/ phi1 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi1)
(* (cos phi2) t_2)
(pow (- (* t_3 t_4) (* t_5 t_0)) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
t_2
(pow (fma t_5 t_0 (* t_3 (- t_4))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi2 / 2.0));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * t_1;
double t_3 = sin((phi1 / 2.0));
double t_4 = cos((phi2 / 2.0));
double t_5 = cos((phi1 / 2.0));
return R * (2.0 * atan2(sqrt(fma(cos(phi1), (cos(phi2) * t_2), pow(((t_3 * t_4) - (t_5 * t_0)), 2.0))), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), t_2, pow(fma(t_5, t_0, (t_3 * -t_4)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi2 / 2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(t_1 * t_1) t_3 = sin(Float64(phi1 / 2.0)) t_4 = cos(Float64(phi2 / 2.0)) t_5 = cos(Float64(phi1 / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), Float64(cos(phi2) * t_2), (Float64(Float64(t_3 * t_4) - Float64(t_5 * t_0)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), t_2, (fma(t_5, t_0, Float64(t_3 * Float64(-t_4))) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi2 / 2.0), $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]}, Block[{t$95$3 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[(N[(t$95$3 * t$95$4), $MachinePrecision] - N[(t$95$5 * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2 + N[Power[N[(t$95$5 * t$95$0 + N[(t$95$3 * (-t$95$4)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\phi_2}{2}\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot t\_1\\
t_3 := \sin \left(\frac{\phi_1}{2}\right)\\
t_4 := \cos \left(\frac{\phi_2}{2}\right)\\
t_5 := \cos \left(\frac{\phi_1}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot t\_2, {\left(t\_3 \cdot t\_4 - t\_5 \cdot t\_0\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_2, {\left(\mathsf{fma}\left(t\_5, t\_0, t\_3 \cdot \left(-t\_4\right)\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.2%
Simplified63.2%
div-sub63.2%
sin-diff64.0%
Applied egg-rr64.0%
*-commutative64.0%
*-commutative64.0%
fmm-def64.0%
distribute-rgt-neg-in64.0%
Simplified64.0%
div-sub64.0%
sin-diff78.7%
Applied egg-rr78.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (/ phi2 2.0)))
(t_1 (cos (/ phi1 2.0)))
(t_2 (sin (/ phi2 2.0)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* t_3 (* t_3 (* (cos phi1) (cos phi2)))))
(t_5 (sin (/ phi1 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (- (* t_5 t_0) (* t_1 t_2)) 2.0) t_4))
(sqrt (- 1.0 (+ (pow (fma t_5 t_0 (* t_2 (- t_1))) 2.0) t_4))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi2 / 2.0));
double t_1 = cos((phi1 / 2.0));
double t_2 = sin((phi2 / 2.0));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = t_3 * (t_3 * (cos(phi1) * cos(phi2)));
double t_5 = sin((phi1 / 2.0));
return R * (2.0 * atan2(sqrt((pow(((t_5 * t_0) - (t_1 * t_2)), 2.0) + t_4)), sqrt((1.0 - (pow(fma(t_5, t_0, (t_2 * -t_1)), 2.0) + t_4)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi2 / 2.0)) t_1 = cos(Float64(phi1 / 2.0)) t_2 = sin(Float64(phi2 / 2.0)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(t_3 * Float64(t_3 * Float64(cos(phi1) * cos(phi2)))) t_5 = sin(Float64(phi1 / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(t_5 * t_0) - Float64(t_1 * t_2)) ^ 2.0) + t_4)), sqrt(Float64(1.0 - Float64((fma(t_5, t_0, Float64(t_2 * Float64(-t_1))) ^ 2.0) + t_4)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 / 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[(t$95$3 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(t$95$5 * t$95$0), $MachinePrecision] - N[(t$95$1 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(t$95$5 * t$95$0 + N[(t$95$2 * (-t$95$1)), $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_2}{2}\right)\\
t_1 := \cos \left(\frac{\phi_1}{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(t\_3 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
t_5 := \sin \left(\frac{\phi_1}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(t\_5 \cdot t\_0 - t\_1 \cdot t\_2\right)}^{2} + t\_4}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(t\_5, t\_0, t\_2 \cdot \left(-t\_1\right)\right)\right)}^{2} + t\_4\right)}}\right)
\end{array}
\end{array}
Initial program 63.2%
div-sub64.0%
sin-diff78.7%
Applied egg-rr63.9%
div-sub64.0%
sin-diff78.7%
Applied egg-rr78.7%
fmm-def78.8%
distribute-rgt-neg-in78.8%
Simplified78.7%
Final simplification78.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)
(* t_0 (* t_0 (* (cos phi1) (cos phi2)))))))
(* 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 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2))));
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 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2))))
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 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0) + (t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2))));
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 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) + (t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2)))) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0) + Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2))))) 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 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0) + (t_0 * (t_0 * (cos(phi1) * cos(phi2)))); 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[(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] + N[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $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(\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\_0 \cdot \left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Initial program 63.2%
div-sub64.0%
sin-diff78.7%
Applied egg-rr63.9%
div-sub64.0%
sin-diff78.7%
Applied egg-rr78.7%
Final simplification78.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))) (t_1 (* t_0 t_0)))
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi1)
(* (cos phi2) t_1)
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
t_1
(pow
(fma
(cos (/ phi1 2.0))
(sin (/ phi2 2.0))
(* (sin (/ phi1 2.0)) (- (cos (/ 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 * t_0;
return R * (2.0 * atan2(sqrt(fma(cos(phi1), (cos(phi2) * t_1), pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), t_1, pow(fma(cos((phi1 / 2.0)), sin((phi2 / 2.0)), (sin((phi1 / 2.0)) * -cos((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 * t_0) return Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), Float64(cos(phi2) * t_1), (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), t_1, (fma(cos(Float64(phi1 / 2.0)), sin(Float64(phi2 / 2.0)), Float64(sin(Float64(phi1 / 2.0)) * Float64(-cos(Float64(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 * t$95$0), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $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] * t$95$1 + N[Power[N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * (-N[Cos[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 t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot t\_1, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_1, {\left(\mathsf{fma}\left(\cos \left(\frac{\phi_1}{2}\right), \sin \left(\frac{\phi_2}{2}\right), \sin \left(\frac{\phi_1}{2}\right) \cdot \left(-\cos \left(\frac{\phi_2}{2}\right)\right)\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.2%
Simplified63.2%
div-sub63.2%
sin-diff64.0%
Applied egg-rr64.0%
*-commutative64.0%
*-commutative64.0%
fmm-def64.0%
distribute-rgt-neg-in64.0%
Simplified64.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt
(-
1.0
(+
t_0
(pow
(-
(* (sin (* phi2 0.5)) (cos (* phi1 0.5)))
(* (cos (* phi2 0.5)) (sin (* phi1 0.5))))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * (cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0));
return R * (2.0 * atan2(sqrt((t_0 + pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt((1.0 - (t_0 + pow(((sin((phi2 * 0.5)) * cos((phi1 * 0.5))) - (cos((phi2 * 0.5)) * 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 = cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0))
code = r * (2.0d0 * atan2(sqrt((t_0 + (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0))), sqrt((1.0d0 - (t_0 + (((sin((phi2 * 0.5d0)) * cos((phi1 * 0.5d0))) - (cos((phi2 * 0.5d0)) * 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.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_0 + Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0))), Math.sqrt((1.0 - (t_0 + Math.pow(((Math.sin((phi2 * 0.5)) * Math.cos((phi1 * 0.5))) - (Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5)))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_0 + math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))), math.sqrt((1.0 - (t_0 + math.pow(((math.sin((phi2 * 0.5)) * math.cos((phi1 * 0.5))) - (math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5)))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_0 + (Float64(Float64(sin(Float64(phi2 * 0.5)) * cos(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5)))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)); tmp = R * (2.0 * atan2(sqrt((t_0 + (sin((0.5 * (phi1 - phi2))) ^ 2.0))), sqrt((1.0 - (t_0 + (((sin((phi2 * 0.5)) * cos((phi1 * 0.5))) - (cos((phi2 * 0.5)) * sin((phi1 * 0.5)))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[Power[N[(N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}{\sqrt{1 - \left(t\_0 + {\left(\sin \left(\phi_2 \cdot 0.5\right) \cdot \cos \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.2%
Simplified63.2%
div-sub63.2%
sin-diff64.0%
Applied egg-rr64.0%
*-commutative64.0%
*-commutative64.0%
fmm-def64.0%
distribute-rgt-neg-in64.0%
Simplified64.0%
Taylor expanded in phi1 around 0 64.0%
Final simplification64.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_1 t_0)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(fabs
(-
1.0
(fma
t_0
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt(((t_1 * (t_1 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(fabs((1.0 - fma(t_0, pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_1 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(abs(Float64(1.0 - fma(t_0, (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(t$95$0 * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $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 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_1 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left|1 - \mathsf{fma}\left(t\_0, {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 63.2%
+-commutative63.2%
associate-*l*63.2%
fma-undefine63.2%
add-sqr-sqrt63.2%
pow1/263.2%
Applied egg-rr63.5%
unpow1/263.5%
unpow263.5%
rem-sqrt-square63.5%
*-commutative63.5%
*-commutative63.5%
Simplified63.5%
Final simplification63.5%
(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 63.2%
associate-*r*63.2%
*-commutative63.2%
Simplified63.2%
unpow263.2%
sin-mult63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
Applied egg-rr63.2%
div-sub63.2%
+-inverses63.2%
cos-063.2%
metadata-eval63.2%
distribute-lft-out63.2%
metadata-eval63.2%
*-rgt-identity63.2%
Simplified63.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* t_0 (* (cos phi1) (cos phi2))))))
(if (or (<= t_0 -0.005) (not (<= t_0 0.013)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(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 (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2)));
double tmp;
if ((t_0 <= -0.005) || !(t_0 <= 0.013)) {
tmp = R * (2.0 * atan2(sqrt((t_1 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), 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((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2)))
if ((t_0 <= (-0.005d0)) .or. (.not. (t_0 <= 0.013d0))) then
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt((1.0d0 - ((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)) + (sin((phi1 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 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 = t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2)));
double tmp;
if ((t_0 <= -0.005) || !(t_0 <= 0.013)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((1.0 - ((Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2))) tmp = 0 if (t_0 <= -0.005) or not (t_0 <= 0.013): tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt((1.0 - ((math.cos(phi1) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + math.pow(math.sin((phi1 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2)))) tmp = 0.0 if ((t_0 <= -0.005) || !(t_0 <= 0.013)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), 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(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2))); tmp = 0.0; if ((t_0 <= -0.005) || ~((t_0 <= 0.013))) tmp = R * (2.0 * atan2(sqrt((t_1 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - ((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin((phi1 * 0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 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[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[t$95$0, -0.005], N[Not[LessEqual[t$95$0, 0.013]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(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[(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[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
\mathbf{if}\;t\_0 \leq -0.005 \lor \neg \left(t\_0 \leq 0.013\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\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{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0050000000000000001 or 0.0129999999999999994 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 59.9%
Taylor expanded in phi2 around 0 46.9%
unpow259.9%
sin-mult59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
Applied egg-rr47.0%
div-sub59.9%
+-inverses59.9%
cos-059.9%
metadata-eval59.9%
distribute-lft-out59.9%
metadata-eval59.9%
*-rgt-identity59.9%
Simplified47.0%
if -0.0050000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.0129999999999999994Initial program 73.4%
Taylor expanded in lambda2 around 0 72.3%
Taylor expanded in lambda1 around 0 71.3%
Final simplification52.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3 (cos (- phi1 phi2)))
(t_4
(sqrt (- 1.0 (+ (* (cos phi1) t_2) (pow (sin (* phi1 0.5)) 2.0)))))
(t_5 (* t_1 (* t_1 t_0))))
(if (<= t_1 -0.005)
(* R (* 2.0 (atan2 (sqrt (fma t_0 t_2 (- 0.5 (* 0.5 t_3)))) t_4)))
(if (<= t_1 0.013)
(*
R
(*
2.0
(atan2
(sqrt (+ t_5 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(* R (* 2.0 (atan2 (sqrt (+ t_5 (- 0.5 (/ t_3 2.0)))) t_4)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = cos((phi1 - phi2));
double t_4 = sqrt((1.0 - ((cos(phi1) * t_2) + pow(sin((phi1 * 0.5)), 2.0))));
double t_5 = t_1 * (t_1 * t_0);
double tmp;
if (t_1 <= -0.005) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, t_2, (0.5 - (0.5 * t_3)))), t_4));
} else if (t_1 <= 0.013) {
tmp = R * (2.0 * atan2(sqrt((t_5 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_5 + (0.5 - (t_3 / 2.0)))), t_4));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = cos(Float64(phi1 - phi2)) t_4 = sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_2) + (sin(Float64(phi1 * 0.5)) ^ 2.0)))) t_5 = Float64(t_1 * Float64(t_1 * t_0)) tmp = 0.0 if (t_1 <= -0.005) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, t_2, Float64(0.5 - Float64(0.5 * t_3)))), t_4))); elseif (t_1 <= 0.013) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_5 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_5 + Float64(0.5 - Float64(t_3 / 2.0)))), t_4))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = 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]}, Block[{t$95$5 = N[(t$95$1 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, -0.005], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * t$95$2 + N[(0.5 - N[(0.5 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 0.013], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$5 + 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[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$5 + N[(0.5 - N[(t$95$3 / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \cos \left(\phi_1 - \phi_2\right)\\
t_4 := \sqrt{1 - \left(\cos \phi_1 \cdot t\_2 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}\\
t_5 := t\_1 \cdot \left(t\_1 \cdot t\_0\right)\\
\mathbf{if}\;t\_1 \leq -0.005:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, t\_2, 0.5 - 0.5 \cdot t\_3\right)}}{t\_4}\right)\\
\mathbf{elif}\;t\_1 \leq 0.013:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_5 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_5 + \left(0.5 - \frac{t\_3}{2}\right)}}{t\_4}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0050000000000000001Initial program 61.9%
Taylor expanded in phi2 around 0 47.5%
unpow261.9%
sin-mult62.0%
div-inv62.0%
metadata-eval62.0%
div-inv62.0%
metadata-eval62.0%
div-inv62.0%
metadata-eval62.0%
div-inv62.0%
metadata-eval62.0%
Applied egg-rr47.5%
div-sub62.0%
+-inverses62.0%
cos-062.0%
metadata-eval62.0%
distribute-lft-out62.0%
metadata-eval62.0%
*-rgt-identity62.0%
Simplified47.5%
add-sqr-sqrt29.2%
pow229.2%
div-inv29.2%
metadata-eval29.2%
Applied egg-rr29.2%
+-commutative29.2%
associate-*l*29.2%
fma-define29.2%
pow229.2%
div-inv29.2%
metadata-eval29.2%
unpow229.2%
add-sqr-sqrt47.5%
*-commutative47.5%
Applied egg-rr47.5%
if -0.0050000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.0129999999999999994Initial program 73.4%
Taylor expanded in lambda2 around 0 72.3%
Taylor expanded in lambda1 around 0 71.3%
if 0.0129999999999999994 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 57.6%
Taylor expanded in phi2 around 0 46.3%
unpow257.7%
sin-mult57.7%
div-inv57.7%
metadata-eval57.7%
div-inv57.7%
metadata-eval57.7%
div-inv57.7%
metadata-eval57.7%
div-inv57.7%
metadata-eval57.7%
Applied egg-rr46.4%
div-sub57.7%
+-inverses57.7%
cos-057.7%
metadata-eval57.7%
distribute-lft-out57.7%
metadata-eval57.7%
*-rgt-identity57.7%
Simplified46.4%
Final simplification52.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= t_2 -0.005) (not (<= t_2 0.013)))
(*
R
(*
2.0
(atan2
(sqrt (+ (+ 0.5 (* (cos (- phi1 phi2)) -0.5)) (* t_0 t_1)))
(sqrt (- 1.0 (+ (* (cos phi1) t_1) (pow (sin (* phi1 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_2 (* t_2 t_0)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((t_2 <= -0.005) || !(t_2 <= 0.013)) {
tmp = R * (2.0 * atan2(sqrt(((0.5 + (cos((phi1 - phi2)) * -0.5)) + (t_0 * t_1))), sqrt((1.0 - ((cos(phi1) * t_1) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_2 * (t_2 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
if ((t_2 <= (-0.005d0)) .or. (.not. (t_2 <= 0.013d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((0.5d0 + (cos((phi1 - phi2)) * (-0.5d0))) + (t_0 * t_1))), sqrt((1.0d0 - ((cos(phi1) * t_1) + (sin((phi1 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((t_2 * (t_2 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((t_2 <= -0.005) || !(t_2 <= 0.013)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((0.5 + (Math.cos((phi1 - phi2)) * -0.5)) + (t_0 * t_1))), Math.sqrt((1.0 - ((Math.cos(phi1) * t_1) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_2 * (t_2 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (t_2 <= -0.005) or not (t_2 <= 0.013): tmp = R * (2.0 * math.atan2(math.sqrt(((0.5 + (math.cos((phi1 - phi2)) * -0.5)) + (t_0 * t_1))), math.sqrt((1.0 - ((math.cos(phi1) * t_1) + math.pow(math.sin((phi1 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((t_2 * (t_2 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((t_2 <= -0.005) || !(t_2 <= 0.013)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 + Float64(cos(Float64(phi1 - phi2)) * -0.5)) + Float64(t_0 * t_1))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_1) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_2 * Float64(t_2 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((t_2 <= -0.005) || ~((t_2 <= 0.013))) tmp = R * (2.0 * atan2(sqrt(((0.5 + (cos((phi1 - phi2)) * -0.5)) + (t_0 * t_1))), sqrt((1.0 - ((cos(phi1) * t_1) + (sin((phi1 * 0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((t_2 * (t_2 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[t$95$2, -0.005], N[Not[LessEqual[t$95$2, 0.013]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(0.5 + N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] + N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $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[(t$95$2 * N[(t$95$2 * 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[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;t\_2 \leq -0.005 \lor \neg \left(t\_2 \leq 0.013\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(0.5 + \cos \left(\phi_1 - \phi_2\right) \cdot -0.5\right) + t\_0 \cdot t\_1}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_1 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 \cdot \left(t\_2 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0050000000000000001 or 0.0129999999999999994 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 59.9%
Taylor expanded in phi2 around 0 46.9%
unpow259.9%
sin-mult59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
Applied egg-rr47.0%
div-sub59.9%
+-inverses59.9%
cos-059.9%
metadata-eval59.9%
distribute-lft-out59.9%
metadata-eval59.9%
*-rgt-identity59.9%
Simplified47.0%
add-sqr-sqrt27.5%
pow227.5%
div-inv27.5%
metadata-eval27.5%
Applied egg-rr27.5%
associate-+l-27.5%
unpow227.5%
add-sqr-sqrt46.8%
*-commutative46.8%
associate-*l*46.8%
pow246.8%
div-inv46.8%
metadata-eval46.8%
Applied egg-rr46.8%
associate--r-47.0%
cancel-sign-sub-inv47.0%
metadata-eval47.0%
*-commutative47.0%
Simplified47.0%
if -0.0050000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.0129999999999999994Initial program 73.4%
Taylor expanded in lambda2 around 0 72.3%
Taylor expanded in lambda1 around 0 71.3%
Final simplification52.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= t_0 -0.005) (not (<= t_0 0.013)))
(*
R
(*
2.0
(atan2
(sqrt (+ 0.5 (fma (cos phi1) t_1 (* (cos phi1) (- 0.5)))))
(sqrt (- 1.0 (+ (* (cos phi1) t_1) (pow (sin (* phi1 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* t_0 (* (cos phi1) (cos phi2))))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((t_0 <= -0.005) || !(t_0 <= 0.013)) {
tmp = R * (2.0 * atan2(sqrt((0.5 + fma(cos(phi1), t_1, (cos(phi1) * -0.5)))), sqrt((1.0 - ((cos(phi1) * t_1) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_0 * (cos(phi1) * cos(phi2)))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - 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 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((t_0 <= -0.005) || !(t_0 <= 0.013)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(0.5 + fma(cos(phi1), t_1, Float64(cos(phi1) * Float64(-0.5))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_1) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2)))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (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[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[t$95$0, -0.005], N[Not[LessEqual[t$95$0, 0.013]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(0.5 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1 + N[(N[Cos[phi1], $MachinePrecision] * (-0.5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $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[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $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[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;t\_0 \leq -0.005 \lor \neg \left(t\_0 \leq 0.013\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{0.5 + \mathsf{fma}\left(\cos \phi_1, t\_1, \cos \phi_1 \cdot \left(-0.5\right)\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_1 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0050000000000000001 or 0.0129999999999999994 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 59.9%
Taylor expanded in phi2 around 0 46.9%
unpow259.9%
sin-mult59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
Applied egg-rr47.0%
div-sub59.9%
+-inverses59.9%
cos-059.9%
metadata-eval59.9%
distribute-lft-out59.9%
metadata-eval59.9%
*-rgt-identity59.9%
Simplified47.0%
add-sqr-sqrt27.5%
pow227.5%
div-inv27.5%
metadata-eval27.5%
Applied egg-rr27.5%
Taylor expanded in phi2 around 0 46.2%
associate--l+46.1%
*-commutative46.1%
fmm-def46.2%
*-commutative46.2%
unpow246.2%
rem-square-sqrt46.4%
Simplified46.4%
if -0.0050000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.0129999999999999994Initial program 73.4%
Taylor expanded in lambda2 around 0 72.3%
Taylor expanded in lambda1 around 0 71.3%
Final simplification52.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi1 -0.00175) (not (<= phi1 1.3e-5)))
(*
R
(*
2.0
(atan2
(sqrt (+ 0.5 (fma (cos phi1) t_0 (* (cos phi1) (- 0.5)))))
(sqrt (- 1.0 (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_1 (* t_1 (* (cos phi1) (cos phi2))))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(- 1.0 (+ (* (cos phi2) t_0) (pow (sin (* phi2 -0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi1 <= -0.00175) || !(phi1 <= 1.3e-5)) {
tmp = R * (2.0 * atan2(sqrt((0.5 + fma(cos(phi1), t_0, (cos(phi1) * -0.5)))), sqrt((1.0 - ((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_1 * (cos(phi1) * cos(phi2)))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - ((cos(phi2) * t_0) + pow(sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi1 <= -0.00175) || !(phi1 <= 1.3e-5)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(0.5 + fma(cos(phi1), t_0, Float64(cos(phi1) * Float64(-0.5))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_1 * Float64(cos(phi1) * cos(phi2)))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_0) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -0.00175], N[Not[LessEqual[phi1, 1.3e-5]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(0.5 + N[(N[Cos[phi1], $MachinePrecision] * t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * (-0.5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$1 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $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[phi2], $MachinePrecision] * t$95$0), $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(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_1 \leq -0.00175 \lor \neg \left(\phi_1 \leq 1.3 \cdot 10^{-5}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{0.5 + \mathsf{fma}\left(\cos \phi_1, t\_0, \cos \phi_1 \cdot \left(-0.5\right)\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_1 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -0.00175000000000000004 or 1.29999999999999992e-5 < phi1 Initial program 44.4%
Taylor expanded in phi2 around 0 45.3%
unpow244.5%
sin-mult44.5%
div-inv44.5%
metadata-eval44.5%
div-inv44.5%
metadata-eval44.5%
div-inv44.5%
metadata-eval44.5%
div-inv44.5%
metadata-eval44.5%
Applied egg-rr45.3%
div-sub44.5%
+-inverses44.5%
cos-044.5%
metadata-eval44.5%
distribute-lft-out44.5%
metadata-eval44.5%
*-rgt-identity44.5%
Simplified45.3%
add-sqr-sqrt15.7%
pow215.7%
div-inv15.7%
metadata-eval15.7%
Applied egg-rr15.7%
Taylor expanded in phi2 around 0 46.1%
associate--l+46.1%
*-commutative46.1%
fmm-def46.2%
*-commutative46.2%
unpow246.2%
rem-square-sqrt46.3%
Simplified46.3%
if -0.00175000000000000004 < phi1 < 1.29999999999999992e-5Initial program 80.7%
Taylor expanded in phi1 around 0 80.7%
Final simplification64.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2
(+
(* t_1 (* t_1 (* (cos phi1) (cos phi2))))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(if (or (<= phi2 -460.0) (not (<= phi2 1.52e+16)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) t_0) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- 1.0 t_2)))))
(*
R
(*
2.0
(atan2
(sqrt t_2)
(sqrt
(- 1.0 (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (t_1 * (t_1 * (cos(phi1) * cos(phi2)))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi2 <= -460.0) || !(phi2 <= 1.52e+16)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - ((cos(phi1) * t_0) + pow(sin((phi1 * 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) * 0.5d0)) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = (t_1 * (t_1 * (cos(phi1) * cos(phi2)))) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)
if ((phi2 <= (-460.0d0)) .or. (.not. (phi2 <= 1.52d+16))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * t_0) + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt((1.0d0 - t_2))))
else
tmp = r * (2.0d0 * atan2(sqrt(t_2), sqrt((1.0d0 - ((cos(phi1) * t_0) + (sin((phi1 * 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.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = (t_1 * (t_1 * (Math.cos(phi1) * Math.cos(phi2)))) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi2 <= -460.0) || !(phi2 <= 1.52e+16)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * t_0) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(t_2), Math.sqrt((1.0 - ((Math.cos(phi1) * t_0) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = (t_1 * (t_1 * (math.cos(phi1) * math.cos(phi2)))) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) tmp = 0 if (phi2 <= -460.0) or not (phi2 <= 1.52e+16): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * t_0) + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((1.0 - t_2)))) else: tmp = R * (2.0 * math.atan2(math.sqrt(t_2), math.sqrt((1.0 - ((math.cos(phi1) * t_0) + math.pow(math.sin((phi1 * 0.5)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(t_1 * Float64(t_1 * Float64(cos(phi1) * cos(phi2)))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) tmp = 0.0 if ((phi2 <= -460.0) || !(phi2 <= 1.52e+16)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = (t_1 * (t_1 * (cos(phi1) * cos(phi2)))) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0); tmp = 0.0; if ((phi2 <= -460.0) || ~((phi2 <= 1.52e+16))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + (sin((phi2 * -0.5)) ^ 2.0))), sqrt((1.0 - t_2)))); else tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - ((cos(phi1) * t_0) + (sin((phi1 * 0.5)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * N[(t$95$1 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -460.0], N[Not[LessEqual[phi2, 1.52e+16]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot \left(t\_1 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -460 \lor \neg \left(\phi_2 \leq 1.52 \cdot 10^{+16}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -460 or 1.52e16 < phi2 Initial program 51.1%
expm1-log1p-u11.3%
div-inv11.3%
metadata-eval11.3%
Applied egg-rr11.3%
Taylor expanded in phi1 around 0 51.7%
if -460 < phi2 < 1.52e16Initial program 76.2%
Taylor expanded in phi2 around 0 76.4%
Final simplification63.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* t_1 (* t_1 (* (cos phi1) (cos phi2))))))
(if (or (<= phi2 -460.0) (not (<= phi2 1.52e+16)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) t_0) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- 1.0 (+ t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt
(- 1.0 (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * (t_1 * (cos(phi1) * cos(phi2)));
double tmp;
if ((phi2 <= -460.0) || !(phi2 <= 1.52e+16)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - (t_2 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin((phi1 / 2.0)), 2.0))), sqrt((1.0 - ((cos(phi1) * t_0) + pow(sin((phi1 * 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) * 0.5d0)) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = t_1 * (t_1 * (cos(phi1) * cos(phi2)))
if ((phi2 <= (-460.0d0)) .or. (.not. (phi2 <= 1.52d+16))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * t_0) + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt((1.0d0 - (t_2 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin((phi1 / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - ((cos(phi1) * t_0) + (sin((phi1 * 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.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * (t_1 * (Math.cos(phi1) * Math.cos(phi2)));
double tmp;
if ((phi2 <= -460.0) || !(phi2 <= 1.52e+16)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * t_0) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((1.0 - (t_2 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin((phi1 / 2.0)), 2.0))), Math.sqrt((1.0 - ((Math.cos(phi1) * t_0) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = t_1 * (t_1 * (math.cos(phi1) * math.cos(phi2))) tmp = 0 if (phi2 <= -460.0) or not (phi2 <= 1.52e+16): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * t_0) + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((1.0 - (t_2 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin((phi1 / 2.0)), 2.0))), math.sqrt((1.0 - ((math.cos(phi1) * t_0) + math.pow(math.sin((phi1 * 0.5)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(t_1 * Float64(t_1 * Float64(cos(phi1) * cos(phi2)))) tmp = 0.0 if ((phi2 <= -460.0) || !(phi2 <= 1.52e+16)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_2 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = t_1 * (t_1 * (cos(phi1) * cos(phi2))); tmp = 0.0; if ((phi2 <= -460.0) || ~((phi2 <= 1.52e+16))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + (sin((phi2 * -0.5)) ^ 2.0))), sqrt((1.0 - (t_2 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((t_2 + (sin((phi1 / 2.0)) ^ 2.0))), sqrt((1.0 - ((cos(phi1) * t_0) + (sin((phi1 * 0.5)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * N[(t$95$1 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -460.0], N[Not[LessEqual[phi2, 1.52e+16]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot \left(t\_1 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
\mathbf{if}\;\phi_2 \leq -460 \lor \neg \left(\phi_2 \leq 1.52 \cdot 10^{+16}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - \left(t\_2 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -460 or 1.52e16 < phi2 Initial program 51.1%
expm1-log1p-u11.3%
div-inv11.3%
metadata-eval11.3%
Applied egg-rr11.3%
Taylor expanded in phi1 around 0 51.7%
if -460 < phi2 < 1.52e16Initial program 76.2%
Taylor expanded in phi2 around 0 76.4%
Taylor expanded in phi1 around inf 75.6%
Final simplification63.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* t_0 t_0) (* (cos phi1) (cos phi2)))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt (- (+ 1.0 (- (/ (cos (- phi1 phi2)) 2.0) 0.5)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (t_0 * t_0) * (cos(phi1) * cos(phi2));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (t_0 * t_0) * (cos(phi1) * cos(phi2))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt(((1.0d0 + ((cos((phi1 - phi2)) / 2.0d0) - 0.5d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (t_0 * t_0) * (Math.cos(phi1) * Math.cos(phi2));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt(((1.0 + ((Math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (t_0 * t_0) * (math.cos(phi1) * math.cos(phi2)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt(((1.0 + ((math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(t_0 * t_0) * Float64(cos(phi1) * cos(phi2))) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(Float64(1.0 + Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (t_0 * t_0) * (cos(phi1) * cos(phi2)); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(t$95$0 * t$95$0), $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(t\_0 \cdot t\_0\right) \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{\left(1 + \left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right)\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 63.2%
associate-*l*63.2%
Simplified63.2%
unpow263.2%
sin-mult63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
Applied egg-rr63.2%
div-sub63.2%
+-inverses63.2%
cos-063.2%
metadata-eval63.2%
distribute-lft-out63.2%
metadata-eval63.2%
*-rgt-identity63.2%
Simplified63.2%
Final simplification63.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* t_0 (* (cos phi1) (cos phi2))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt (- 1.0 (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2)));
return R * (2.0 * atan2(sqrt((t_1 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - (t_1 + 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
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2)))
code = r * (2.0d0 * atan2(sqrt((t_1 + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt((1.0d0 - (t_1 + (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));
double t_1 = t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2)));
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((1.0 - (t_1 + 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)) t_1 = t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2))) return R * (2.0 * math.atan2(math.sqrt((t_1 + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt((1.0 - (t_1 + 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)) t_1 = Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2)))) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(1.0 - Float64(t_1 + (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)); t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2))); tmp = R * (2.0 * atan2(sqrt((t_1 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - (t_1 + (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]}, Block[{t$95$1 = N[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{1 - \left(t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.2%
unpow263.2%
sin-mult63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
Applied egg-rr61.0%
div-sub63.2%
+-inverses63.2%
cos-063.2%
metadata-eval63.2%
distribute-lft-out63.2%
metadata-eval63.2%
*-rgt-identity63.2%
Simplified61.0%
Final simplification61.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* t_0 t_0) (* (cos phi1) (cos phi2)))))
(*
R
(*
2.0
(atan2
(sqrt (+ (- 0.5 (/ (cos (- phi1 phi2)) 2.0)) t_1))
(sqrt (- (- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (t_0 * t_0) * (cos(phi1) * cos(phi2));
return R * (2.0 * atan2(sqrt(((0.5 - (cos((phi1 - phi2)) / 2.0)) + t_1)), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (t_0 * t_0) * (cos(phi1) * cos(phi2))
code = r * (2.0d0 * atan2(sqrt(((0.5d0 - (cos((phi1 - phi2)) / 2.0d0)) + t_1)), sqrt(((1.0d0 - (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (t_0 * t_0) * (Math.cos(phi1) * Math.cos(phi2));
return 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 - phi2) / 2.0)), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (t_0 * t_0) * (math.cos(phi1) * math.cos(phi2)) return 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 - phi2) / 2.0)), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(t_0 * t_0) * Float64(cos(phi1) * cos(phi2))) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)) + t_1)), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (t_0 * t_0) * (cos(phi1) * cos(phi2)); tmp = R * (2.0 * atan2(sqrt(((0.5 - (cos((phi1 - phi2)) / 2.0)) + t_1)), sqrt(((1.0 - (sin(((phi1 - phi2) / 2.0)) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(t$95$0 * t$95$0), $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $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[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(t\_0 \cdot t\_0\right) \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\\
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{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 63.2%
associate-*l*63.2%
Simplified63.2%
unpow263.2%
sin-mult63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
Applied egg-rr61.0%
div-sub63.2%
+-inverses63.2%
cos-063.2%
metadata-eval63.2%
distribute-lft-out63.2%
metadata-eval63.2%
*-rgt-identity63.2%
Simplified61.0%
Final simplification61.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* t_0 (* (cos phi1) (cos phi2))))))
(if (<= t_0 0.08)
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(*
R
(*
2.0
(atan2
(* (sin (* (- lambda1 lambda2) 0.5)) (sqrt (cos phi2)))
(sqrt
(- 1.0 (+ t_1 (pow (sin (/ 1.0 (/ 2.0 (- 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 = t_0 * (t_0 * (cos(phi1) * cos(phi2)));
double tmp;
if (t_0 <= 0.08) {
tmp = R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2((sin(((lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt((1.0 - (t_1 + pow(sin((1.0 / (2.0 / (phi1 - phi2)))), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2)))
if (t_0 <= 0.08d0) then
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2((sin(((lambda1 - lambda2) * 0.5d0)) * sqrt(cos(phi2))), sqrt((1.0d0 - (t_1 + (sin((1.0d0 / (2.0d0 / (phi1 - phi2)))) ** 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 = t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2)));
double tmp;
if (t_0 <= 0.08) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2((Math.sin(((lambda1 - lambda2) * 0.5)) * Math.sqrt(Math.cos(phi2))), Math.sqrt((1.0 - (t_1 + Math.pow(Math.sin((1.0 / (2.0 / (phi1 - phi2)))), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2))) tmp = 0 if t_0 <= 0.08: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) else: tmp = R * (2.0 * math.atan2((math.sin(((lambda1 - lambda2) * 0.5)) * math.sqrt(math.cos(phi2))), math.sqrt((1.0 - (t_1 + math.pow(math.sin((1.0 / (2.0 / (phi1 - phi2)))), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(t_0 * Float64(cos(phi1) * cos(phi2)))) tmp = 0.0 if (t_0 <= 0.08) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 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(t_1 + (sin(Float64(1.0 / Float64(2.0 / Float64(phi1 - phi2)))) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * (t_0 * (cos(phi1) * cos(phi2))); tmp = 0.0; if (t_0 <= 0.08) tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); else tmp = R * (2.0 * atan2((sin(((lambda1 - lambda2) * 0.5)) * sqrt(cos(phi2))), sqrt((1.0 - (t_1 + (sin((1.0 / (2.0 / (phi1 - phi2)))) ^ 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[(t$95$0 * N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$0, 0.08], 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[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $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[(t$95$1 + N[Power[N[Sin[N[(1.0 / N[(2.0 / N[(phi1 - phi2), $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(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right)\\
\mathbf{if}\;t\_0 \leq 0.08:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\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(t\_1 + {\sin \left(\frac{1}{\frac{2}{\phi_1 - \phi_2}}\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.0800000000000000017Initial program 66.0%
Taylor expanded in lambda2 around 0 46.9%
Taylor expanded in lambda1 around 0 40.0%
if 0.0800000000000000017 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 57.4%
clear-num53.5%
inv-pow53.2%
Applied egg-rr53.2%
unpow-153.5%
Simplified53.5%
Taylor expanded in phi1 around inf 40.0%
Taylor expanded in phi1 around 0 27.8%
Final simplification36.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* t_0 (* (cos phi1) (cos phi2))))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt(((t_0 * (t_0 * (cos(phi1) * cos(phi2)))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((t_0 * (t_0 * (cos(phi1) * cos(phi2)))) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_0 * (Math.cos(phi1) * Math.cos(phi2)))) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt(((t_0 * (t_0 * (math.cos(phi1) * math.cos(phi2)))) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.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(t_0 * Float64(cos(phi1) * cos(phi2)))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_0 * (cos(phi1) * cos(phi2)))) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (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[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $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[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 63.2%
Taylor expanded in lambda2 around 0 41.3%
Taylor expanded in lambda1 around 0 33.9%
Final simplification33.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2)))))
(*
2.0
(*
R
(atan2
t_0
(sqrt
(-
1.0
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
return 2.0 * (R * atan2(t_0, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0))) + 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((0.5d0 * (phi1 - phi2)))
code = 2.0d0 * (r * atan2(t_0, sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0))) + (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((0.5 * (phi1 - phi2)));
return 2.0 * (R * Math.atan2(t_0, Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + Math.pow(t_0, 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (phi1 - phi2))) return 2.0 * (R * math.atan2(t_0, math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + math.pow(t_0, 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) return Float64(2.0 * Float64(R * atan(t_0, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))) + (t_0 ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))); tmp = 2.0 * (R * atan2(t_0, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0))) + (t_0 ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(2.0 * N[(R * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
2 \cdot \left(R \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right) + {t\_0}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.2%
associate-*r*63.2%
*-commutative63.2%
Simplified63.2%
Taylor expanded in lambda1 around 0 45.9%
Taylor expanded in lambda2 around 0 16.0%
Taylor expanded in phi1 around 0 16.0%
Final simplification16.0%
herbie shell --seed 2024180
(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))))))))))