
(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 21 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ phi1 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (cos (/ phi2 2.0)))
(t_3 (cos (/ phi1 2.0)))
(t_4 (sin (/ phi2 2.0)))
(t_5 (sin (/ (- lambda1 lambda2) 2.0))))
(*
(atan2
(sqrt (fma t_1 (* t_5 t_5) (pow (- (* t_0 t_2) (* t_3 t_4)) 2.0)))
(sqrt
(-
1.0
(fma
t_1
(-
0.5
(*
0.5
(+ (* (cos lambda1) (cos lambda2)) (* (sin lambda1) (sin lambda2)))))
(pow (fma t_0 t_2 (* t_4 (- t_3))) 2.0)))))
(* 2.0 R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = cos((phi2 / 2.0));
double t_3 = cos((phi1 / 2.0));
double t_4 = sin((phi2 / 2.0));
double t_5 = sin(((lambda1 - lambda2) / 2.0));
return atan2(sqrt(fma(t_1, (t_5 * t_5), pow(((t_0 * t_2) - (t_3 * t_4)), 2.0))), sqrt((1.0 - fma(t_1, (0.5 - (0.5 * ((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))))), pow(fma(t_0, t_2, (t_4 * -t_3)), 2.0))))) * (2.0 * R);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = cos(Float64(phi2 / 2.0)) t_3 = cos(Float64(phi1 / 2.0)) t_4 = sin(Float64(phi2 / 2.0)) t_5 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(atan(sqrt(fma(t_1, Float64(t_5 * t_5), (Float64(Float64(t_0 * t_2) - Float64(t_3 * t_4)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_1, Float64(0.5 - Float64(0.5 * Float64(Float64(cos(lambda1) * cos(lambda2)) + Float64(sin(lambda1) * sin(lambda2))))), (fma(t_0, t_2, Float64(t_4 * Float64(-t_3))) ^ 2.0))))) * Float64(2.0 * R)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[(t$95$5 * t$95$5), $MachinePrecision] + N[Power[N[(N[(t$95$0 * t$95$2), $MachinePrecision] - N[(t$95$3 * t$95$4), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * N[(0.5 - N[(0.5 * N[(N[(N[Cos[lambda1], $MachinePrecision] * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[lambda1], $MachinePrecision] * N[Sin[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$0 * t$95$2 + N[(t$95$4 * (-t$95$3)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\phi_1}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \cos \left(\frac{\phi_2}{2}\right)\\
t_3 := \cos \left(\frac{\phi_1}{2}\right)\\
t_4 := \sin \left(\frac{\phi_2}{2}\right)\\
t_5 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_5 \cdot t\_5, {\left(t\_0 \cdot t\_2 - t\_3 \cdot t\_4\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1, 0.5 - 0.5 \cdot \left(\cos \lambda_1 \cdot \cos \lambda_2 + \sin \lambda_1 \cdot \sin \lambda_2\right), {\left(\mathsf{fma}\left(t\_0, t\_2, t\_4 \cdot \left(-t\_3\right)\right)\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)
\end{array}
\end{array}
Initial program 62.6%
associate-*r*62.6%
*-commutative62.6%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr63.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr78.6%
fmm-def78.6%
distribute-rgt-neg-in78.6%
Simplified78.6%
sqr-sin-a78.6%
cos-278.6%
cos-sum78.6%
add-log-exp24.5%
add-log-exp24.5%
sum-log24.5%
exp-sqrt24.5%
exp-sqrt24.5%
add-sqr-sqrt24.5%
add-log-exp78.6%
Applied egg-rr78.6%
cos-diff79.2%
Applied egg-rr79.2%
Final simplification79.2%
(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 (sin (/ phi1 2.0))))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
(* (cos phi2) (+ (exp (log1p (cos phi1))) -1.0))
(* t_3 t_3)
(pow (- (* t_4 t_0) (* t_1 t_2)) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(pow (fma t_4 t_0 (* t_2 (- t_1))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi2 / 2.0));
double t_1 = cos((phi1 / 2.0));
double t_2 = sin((phi2 / 2.0));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = sin((phi1 / 2.0));
return (2.0 * R) * atan2(sqrt(fma((cos(phi2) * (exp(log1p(cos(phi1))) + -1.0)), (t_3 * t_3), pow(((t_4 * t_0) - (t_1 * t_2)), 2.0))), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), (0.5 - (0.5 * cos((lambda1 - lambda2)))), pow(fma(t_4, t_0, (t_2 * -t_1)), 2.0)))));
}
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 = sin(Float64(phi1 / 2.0)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(Float64(cos(phi2) * Float64(exp(log1p(cos(phi1))) + -1.0)), Float64(t_3 * t_3), (Float64(Float64(t_4 * t_0) - Float64(t_1 * t_2)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), (fma(t_4, t_0, Float64(t_2 * Float64(-t_1))) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[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[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[Exp[N[Log[1 + N[Cos[phi1], $MachinePrecision]], $MachinePrecision]], $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision] * N[(t$95$3 * t$95$3), $MachinePrecision] + N[Power[N[(N[(t$95$4 * t$95$0), $MachinePrecision] - N[(t$95$1 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$4 * t$95$0 + N[(t$95$2 * (-t$95$1)), $MachinePrecision]), $MachinePrecision], 2.0], $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 := \sin \left(\frac{\phi_1}{2}\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2 \cdot \left(e^{\mathsf{log1p}\left(\cos \phi_1\right)} + -1\right), t\_3 \cdot t\_3, {\left(t\_4 \cdot t\_0 - t\_1 \cdot t\_2\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\left(\mathsf{fma}\left(t\_4, t\_0, t\_2 \cdot \left(-t\_1\right)\right)\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.6%
associate-*r*62.6%
*-commutative62.6%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr63.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr78.6%
fmm-def78.6%
distribute-rgt-neg-in78.6%
Simplified78.6%
sqr-sin-a78.6%
cos-278.6%
cos-sum78.6%
add-log-exp24.5%
add-log-exp24.5%
sum-log24.5%
exp-sqrt24.5%
exp-sqrt24.5%
add-sqr-sqrt24.5%
add-log-exp78.6%
Applied egg-rr78.6%
expm1-log1p-u78.6%
expm1-undefine78.6%
Applied egg-rr78.6%
Final simplification78.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ phi2 2.0)))
(t_1 (cos (/ phi2 2.0)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (cos (/ phi1 2.0))))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
t_2
(* t_3 t_3)
(pow (- (* t_1 (expm1 (log1p (sin (* phi1 0.5))))) (* t_4 t_0)) 2.0)))
(sqrt
(-
1.0
(fma
t_2
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(pow (fma (sin (/ phi1 2.0)) t_1 (* t_0 (- 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 = cos((phi2 / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = cos((phi1 / 2.0));
return (2.0 * R) * atan2(sqrt(fma(t_2, (t_3 * t_3), pow(((t_1 * expm1(log1p(sin((phi1 * 0.5))))) - (t_4 * t_0)), 2.0))), sqrt((1.0 - fma(t_2, (0.5 - (0.5 * cos((lambda1 - lambda2)))), pow(fma(sin((phi1 / 2.0)), t_1, (t_0 * -t_4)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi2 / 2.0)) t_1 = cos(Float64(phi2 / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = cos(Float64(phi1 / 2.0)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_2, Float64(t_3 * t_3), (Float64(Float64(t_1 * expm1(log1p(sin(Float64(phi1 * 0.5))))) - Float64(t_4 * t_0)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_2, Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), (fma(sin(Float64(phi1 / 2.0)), t_1, Float64(t_0 * 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[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$2 * N[(t$95$3 * t$95$3), $MachinePrecision] + N[Power[N[(N[(t$95$1 * N[(Exp[N[Log[1 + N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]] - 1), $MachinePrecision]), $MachinePrecision] - N[(t$95$4 * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * t$95$1 + N[(t$95$0 * (-t$95$4)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\phi_2}{2}\right)\\
t_1 := \cos \left(\frac{\phi_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \cos \left(\frac{\phi_1}{2}\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, t\_3 \cdot t\_3, {\left(t\_1 \cdot \mathsf{expm1}\left(\mathsf{log1p}\left(\sin \left(\phi_1 \cdot 0.5\right)\right)\right) - t\_4 \cdot t\_0\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_2, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\left(\mathsf{fma}\left(\sin \left(\frac{\phi_1}{2}\right), t\_1, t\_0 \cdot \left(-t\_4\right)\right)\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.6%
associate-*r*62.6%
*-commutative62.6%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr63.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr78.6%
fmm-def78.6%
distribute-rgt-neg-in78.6%
Simplified78.6%
sqr-sin-a78.6%
cos-278.6%
cos-sum78.6%
add-log-exp24.5%
add-log-exp24.5%
sum-log24.5%
exp-sqrt24.5%
exp-sqrt24.5%
add-sqr-sqrt24.5%
add-log-exp78.6%
Applied egg-rr78.6%
expm1-log1p-u78.6%
expm1-undefine78.0%
div-inv78.0%
metadata-eval78.0%
Applied egg-rr78.0%
expm1-define78.6%
Simplified78.6%
Final simplification78.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ phi2 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (cos (/ phi1 2.0))))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
t_1
(* t_2 t_2)
(pow
(-
(expm1 (log1p (* (sin (* phi1 0.5)) (cos (* phi2 0.5)))))
(* t_3 t_0))
2.0)))
(sqrt
(-
1.0
(fma
t_1
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(pow
(fma (sin (/ phi1 2.0)) (cos (/ phi2 2.0)) (* t_0 (- t_3)))
2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi2 / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = cos((phi1 / 2.0));
return (2.0 * R) * atan2(sqrt(fma(t_1, (t_2 * t_2), pow((expm1(log1p((sin((phi1 * 0.5)) * cos((phi2 * 0.5))))) - (t_3 * t_0)), 2.0))), sqrt((1.0 - fma(t_1, (0.5 - (0.5 * cos((lambda1 - lambda2)))), pow(fma(sin((phi1 / 2.0)), cos((phi2 / 2.0)), (t_0 * -t_3)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi2 / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = cos(Float64(phi1 / 2.0)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_1, Float64(t_2 * t_2), (Float64(expm1(log1p(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))))) - Float64(t_3 * t_0)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_1, Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), (fma(sin(Float64(phi1 / 2.0)), cos(Float64(phi2 / 2.0)), Float64(t_0 * Float64(-t_3))) ^ 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$1 * N[(t$95$2 * t$95$2), $MachinePrecision] + N[Power[N[(N[(Exp[N[Log[1 + N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]] - 1), $MachinePrecision] - N[(t$95$3 * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision] + N[(t$95$0 * (-t$95$3)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\phi_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \cos \left(\frac{\phi_1}{2}\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_2 \cdot t\_2, {\left(\mathsf{expm1}\left(\mathsf{log1p}\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right)\right)\right) - t\_3 \cdot t\_0\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\left(\mathsf{fma}\left(\sin \left(\frac{\phi_1}{2}\right), \cos \left(\frac{\phi_2}{2}\right), t\_0 \cdot \left(-t\_3\right)\right)\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.6%
associate-*r*62.6%
*-commutative62.6%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr63.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr78.6%
fmm-def78.6%
distribute-rgt-neg-in78.6%
Simplified78.6%
sqr-sin-a78.6%
cos-278.6%
cos-sum78.6%
add-log-exp24.5%
add-log-exp24.5%
sum-log24.5%
exp-sqrt24.5%
exp-sqrt24.5%
add-sqr-sqrt24.5%
add-log-exp78.6%
Applied egg-rr78.6%
expm1-log1p-u78.6%
div-inv78.6%
metadata-eval78.6%
div-inv78.6%
metadata-eval78.6%
Applied egg-rr78.6%
Final simplification78.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ phi2 2.0)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (sin (/ phi1 2.0)))
(t_3 (cos (/ phi1 2.0)))
(t_4 (* (cos phi1) (cos phi2)))
(t_5 (cos (/ phi2 2.0))))
(*
(* 2.0 R)
(atan2
(sqrt (fma t_4 (* t_1 t_1) (pow (- (* t_2 t_5) (* t_3 t_0)) 2.0)))
(sqrt
(-
1.0
(fma
t_4
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(pow (fma t_2 t_5 (* t_0 (- t_3))) 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 = sin((phi1 / 2.0));
double t_3 = cos((phi1 / 2.0));
double t_4 = cos(phi1) * cos(phi2);
double t_5 = cos((phi2 / 2.0));
return (2.0 * R) * atan2(sqrt(fma(t_4, (t_1 * t_1), pow(((t_2 * t_5) - (t_3 * t_0)), 2.0))), sqrt((1.0 - fma(t_4, (0.5 - (0.5 * cos((lambda1 - lambda2)))), pow(fma(t_2, t_5, (t_0 * -t_3)), 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 = sin(Float64(phi1 / 2.0)) t_3 = cos(Float64(phi1 / 2.0)) t_4 = Float64(cos(phi1) * cos(phi2)) t_5 = cos(Float64(phi2 / 2.0)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_4, Float64(t_1 * t_1), (Float64(Float64(t_2 * t_5) - Float64(t_3 * t_0)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_4, Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), (fma(t_2, t_5, Float64(t_0 * Float64(-t_3))) ^ 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[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$4 * N[(t$95$1 * t$95$1), $MachinePrecision] + N[Power[N[(N[(t$95$2 * t$95$5), $MachinePrecision] - N[(t$95$3 * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$4 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$2 * t$95$5 + N[(t$95$0 * (-t$95$3)), $MachinePrecision]), $MachinePrecision], 2.0], $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 := \sin \left(\frac{\phi_1}{2}\right)\\
t_3 := \cos \left(\frac{\phi_1}{2}\right)\\
t_4 := \cos \phi_1 \cdot \cos \phi_2\\
t_5 := \cos \left(\frac{\phi_2}{2}\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_4, t\_1 \cdot t\_1, {\left(t\_2 \cdot t\_5 - t\_3 \cdot t\_0\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_4, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\left(\mathsf{fma}\left(t\_2, t\_5, t\_0 \cdot \left(-t\_3\right)\right)\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.6%
associate-*r*62.6%
*-commutative62.6%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr63.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr78.6%
fmm-def78.6%
distribute-rgt-neg-in78.6%
Simplified78.6%
sqr-sin-a78.6%
cos-278.6%
cos-sum78.6%
add-log-exp24.5%
add-log-exp24.5%
sum-log24.5%
exp-sqrt24.5%
exp-sqrt24.5%
add-sqr-sqrt24.5%
add-log-exp78.6%
Applied egg-rr78.6%
Final simplification78.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(*
2.0
(*
R
(atan2
(sqrt
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
t_0))
(sqrt
(+
1.0
(-
(*
(cos phi1)
(* (cos phi2) (- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))
t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
return 2.0 * (R * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0))) + t_0)), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) - t_0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = ((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
code = 2.0d0 * (r * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0))) + t_0)), sqrt((1.0d0 + ((cos(phi1) * (cos(phi2) * ((0.5d0 * cos((lambda1 - lambda2))) - 0.5d0))) - t_0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
return 2.0 * (R * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + t_0)), Math.sqrt((1.0 + ((Math.cos(phi1) * (Math.cos(phi2) * ((0.5 * Math.cos((lambda1 - lambda2))) - 0.5))) - t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) return 2.0 * (R * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + t_0)), math.sqrt((1.0 + ((math.cos(phi1) * (math.cos(phi2) * ((0.5 * math.cos((lambda1 - lambda2))) - 0.5))) - t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 return Float64(2.0 * Float64(R * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))) + t_0)), sqrt(Float64(1.0 + Float64(Float64(cos(phi1) * Float64(cos(phi2) * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))) - t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; tmp = 2.0 * (R * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0))) + t_0)), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) - t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(2.0 * N[(R * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{\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}}{\sqrt{1 + \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)\right) - t\_0\right)}}\right)
\end{array}
\end{array}
Initial program 62.6%
associate-*r*62.6%
*-commutative62.6%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr63.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr78.6%
fmm-def78.6%
distribute-rgt-neg-in78.6%
Simplified78.6%
sqr-sin-a78.6%
cos-278.6%
cos-sum78.6%
add-log-exp24.5%
add-log-exp24.5%
sum-log24.5%
exp-sqrt24.5%
exp-sqrt24.5%
add-sqr-sqrt24.5%
add-log-exp78.6%
Applied egg-rr78.6%
Taylor expanded in phi1 around 0 78.6%
Final simplification78.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
t_1
(* t_0 t_0)
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)))
(sqrt
(-
1.0
(fma
t_1
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
return (2.0 * R) * atan2(sqrt(fma(t_1, (t_0 * t_0), pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0))), sqrt((1.0 - fma(t_1, (0.5 - (0.5 * cos((lambda1 - lambda2)))), (0.5 - (cos((phi1 - phi2)) / 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_1, Float64(t_0 * t_0), (Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0))), sqrt(Float64(1.0 - fma(t_1, Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision] + N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0 \cdot t\_0, {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), 0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}
\end{array}
\end{array}
Initial program 62.6%
associate-*r*62.6%
*-commutative62.6%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr63.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr78.6%
fmm-def78.6%
distribute-rgt-neg-in78.6%
Simplified78.6%
sqr-sin-a78.6%
cos-278.6%
cos-sum78.6%
add-log-exp24.5%
add-log-exp24.5%
sum-log24.5%
exp-sqrt24.5%
exp-sqrt24.5%
add-sqr-sqrt24.5%
add-log-exp78.6%
Applied egg-rr78.6%
distribute-rgt-neg-out78.6%
fmm-def78.6%
sin-diff63.6%
div-sub63.6%
unpow263.6%
sin-mult63.7%
Applied egg-rr63.7%
div-sub63.7%
+-inverses63.7%
+-inverses63.7%
+-inverses63.7%
cos-063.7%
metadata-eval63.7%
distribute-rgt-out63.7%
metadata-eval63.7%
*-rgt-identity63.7%
Simplified63.7%
Final simplification63.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))))
(*
(* 2.0 R)
(atan2
(sqrt
(+
t_0
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(sqrt (- 1.0 (+ t_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) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0));
return (2.0 * R) * atan2(sqrt((t_0 + pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0))), sqrt((1.0 - (t_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 = cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0))
code = (2.0d0 * r) * atan2(sqrt((t_0 + (((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0))), sqrt((1.0d0 - (t_0 + (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.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0));
return (2.0 * R) * Math.atan2(Math.sqrt((t_0 + Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0))), Math.sqrt((1.0 - (t_0 + Math.pow(Math.sin((0.5 * (phi1 - phi2))), 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 (2.0 * R) * math.atan2(math.sqrt((t_0 + math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0))), math.sqrt((1.0 - (t_0 + math.pow(math.sin((0.5 * (phi1 - phi2))), 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(Float64(2.0 * R) * atan(sqrt(Float64(t_0 + (Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_0 + (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 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 = (2.0 * R) * atan2(sqrt((t_0 + (((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0))), sqrt((1.0 - (t_0 + (sin((0.5 * (phi1 - phi2))) ^ 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[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$0 + N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$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 \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}}}{\sqrt{1 - \left(t\_0 + {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.6%
associate-*r*62.6%
*-commutative62.6%
Simplified62.6%
div-sub62.6%
sin-diff63.6%
Applied egg-rr63.6%
Taylor expanded in phi1 around 0 63.6%
Final simplification63.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_1))))
(sqrt
(fabs
(-
1.0
(fma
(+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))
t_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((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_1)))), sqrt(fabs((1.0 - fma((0.5 + (cos((lambda1 - lambda2)) * -0.5)), t_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((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_1)))), sqrt(abs(Float64(1.0 - fma(Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)), t_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[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] * t$95$0 + 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{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left|1 - \mathsf{fma}\left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5, t\_0, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 62.6%
associate-*l*62.6%
Simplified62.5%
Applied egg-rr63.1%
unpow1/263.1%
unpow263.1%
rem-sqrt-square63.1%
cancel-sign-sub-inv63.1%
metadata-eval63.1%
*-commutative63.1%
Simplified63.1%
Final simplification63.1%
(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))
(t_2 (* (cos phi1) t_1)))
(if (or (<= phi1 -3.9e-5) (not (<= phi1 0.00025)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) t_2)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt
(- 1.0 (+ (* (cos phi2) t_1) (pow (sin (* phi2 -0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = cos(phi1) * t_1;
double tmp;
if ((phi1 <= -3.9e-5) || !(phi1 <= 0.00025)) {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - ((cos(phi2) * t_1) + pow(sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
t_2 = cos(phi1) * t_1
if ((phi1 <= (-3.9d-5)) .or. (.not. (phi1 <= 0.00025d0))) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - t_2))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0d0 - ((cos(phi2) * t_1) + (sin((phi2 * (-0.5d0))) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = Math.cos(phi1) * t_1;
double tmp;
if ((phi1 <= -3.9e-5) || !(phi1 <= 0.00025)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - t_2))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)))), Math.sqrt((1.0 - ((Math.cos(phi2) * t_1) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) t_2 = math.cos(phi1) * t_1 tmp = 0 if (phi1 <= -3.9e-5) or not (phi1 <= 0.00025): tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - t_2)))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt((1.0 - ((math.cos(phi2) * t_1) + math.pow(math.sin((phi2 * -0.5)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = Float64(cos(phi1) * t_1) tmp = 0.0 if ((phi1 <= -3.9e-5) || !(phi1 <= 0.00025)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_1) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; t_2 = cos(phi1) * t_1; tmp = 0.0; if ((phi1 <= -3.9e-5) || ~((phi1 <= 0.00025))) tmp = R * (2.0 * atan2(sqrt((t_2 + (sin((phi1 * 0.5)) ^ 2.0))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - t_2)))); else tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - ((cos(phi2) * t_1) + (sin((phi2 * -0.5)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]}, If[Or[LessEqual[phi1, -3.9e-5], N[Not[LessEqual[phi1, 0.00025]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \cos \phi_1 \cdot t\_1\\
\mathbf{if}\;\phi_1 \leq -3.9 \cdot 10^{-5} \lor \neg \left(\phi_1 \leq 0.00025\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_1 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -3.8999999999999999e-5 or 2.5000000000000001e-4 < phi1 Initial program 46.9%
Taylor expanded in phi1 around inf 47.1%
expm1-log1p-u47.1%
associate--r+47.1%
unpow247.1%
1-sub-sin47.2%
pow247.2%
div-inv47.2%
metadata-eval47.2%
associate-*r*47.2%
associate-*l*47.2%
pow247.2%
Applied egg-rr47.2%
associate-*r*47.2%
*-commutative47.2%
Simplified47.2%
Taylor expanded in phi2 around 0 48.0%
*-commutative48.0%
Simplified48.0%
Taylor expanded in phi2 around 0 48.9%
if -3.8999999999999999e-5 < phi1 < 2.5000000000000001e-4Initial program 79.2%
associate-*l*79.2%
Simplified79.2%
Taylor expanded in phi1 around 0 79.2%
Final simplification63.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt (- (+ 1.0 (- (/ (cos (- phi1 phi2)) 2.0) 0.5)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt(((1.0d0 + ((cos((phi1 - phi2)) / 2.0d0) - 0.5d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt(((1.0 + ((Math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt(((1.0 + ((math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(Float64(1.0 + Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{\left(1 + \left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right)\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.6%
associate-*l*62.6%
Simplified62.5%
unpow262.5%
sin-mult62.6%
div-inv62.6%
metadata-eval62.6%
div-inv62.6%
metadata-eval62.6%
div-inv62.6%
metadata-eval62.6%
div-inv62.6%
metadata-eval62.6%
Applied egg-rr62.6%
div-sub62.6%
+-inverses62.6%
cos-062.6%
metadata-eval62.6%
distribute-lft-out62.6%
metadata-eval62.6%
*-rgt-identity62.6%
Simplified62.6%
Final simplification62.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_0 (* t_1 t_1))))
(sqrt
(-
(- 1.0 t_2)
(* t_0 (+ -1.0 (+ (* (cos (- lambda1 lambda2)) -0.5) 1.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - t_2) - (t_0 * (-1.0 + ((cos((lambda1 - lambda2)) * -0.5) + 1.5)))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0d0 - t_2) - (t_0 * ((-1.0d0) + ((cos((lambda1 - lambda2)) * (-0.5d0)) + 1.5d0)))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((t_2 + (t_0 * (t_1 * t_1)))), Math.sqrt(((1.0 - t_2) - (t_0 * (-1.0 + ((Math.cos((lambda1 - lambda2)) * -0.5) + 1.5)))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) return R * (2.0 * math.atan2(math.sqrt((t_2 + (t_0 * (t_1 * t_1)))), math.sqrt(((1.0 - t_2) - (t_0 * (-1.0 + ((math.cos((lambda1 - lambda2)) * -0.5) + 1.5)))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_0 * Float64(t_1 * t_1)))), sqrt(Float64(Float64(1.0 - t_2) - Float64(t_0 * Float64(-1.0 + Float64(Float64(cos(Float64(lambda1 - lambda2)) * -0.5) + 1.5)))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = R * (2.0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - t_2) - (t_0 * (-1.0 + ((cos((lambda1 - lambda2)) * -0.5) + 1.5))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$2), $MachinePrecision] - N[(t$95$0 * N[(-1.0 + N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision] + 1.5), $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)\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left(1 - t\_2\right) - t\_0 \cdot \left(-1 + \left(\cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5 + 1.5\right)\right)}}\right)
\end{array}
\end{array}
Initial program 62.6%
associate-*l*62.6%
Simplified62.5%
expm1-log1p-u62.5%
expm1-undefine62.5%
Applied egg-rr62.5%
sub-neg62.5%
log1p-undefine62.5%
rem-exp-log62.5%
sub-neg62.5%
associate-+r+62.6%
metadata-eval62.6%
distribute-lft-neg-in62.6%
metadata-eval62.6%
metadata-eval62.6%
Simplified62.6%
Final simplification62.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (- lambda1 lambda2) 0.5))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -2.05e-5) (not (<= phi2 0.000105)))
(*
(* 2.0 R)
(atan2
(sqrt
(+ (* (cos phi2) (pow (sin t_0) 2.0)) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
1.0
(fma
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
t_1
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_2 (* t_1 t_2))))
(sqrt
(+
(pow (cos (* phi1 0.5)) 2.0)
(* (cos phi1) (- (/ (cos (* 2.0 t_0)) 2.0) 0.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (lambda1 - lambda2) * 0.5;
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -2.05e-5) || !(phi2 <= 0.000105)) {
tmp = (2.0 * R) * atan2(sqrt(((cos(phi2) * pow(sin(t_0), 2.0)) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - fma((0.5 - (0.5 * cos((lambda1 - lambda2)))), t_1, pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_2 * (t_1 * t_2)))), sqrt((pow(cos((phi1 * 0.5)), 2.0) + (cos(phi1) * ((cos((2.0 * t_0)) / 2.0) - 0.5))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(lambda1 - lambda2) * 0.5) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -2.05e-5) || !(phi2 <= 0.000105)) tmp = Float64(Float64(2.0 * R) * atan(sqrt(Float64(Float64(cos(phi2) * (sin(t_0) ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), t_1, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_2 * Float64(t_1 * t_2)))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * Float64(Float64(cos(Float64(2.0 * t_0)) / 2.0) - 0.5))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -2.05e-5], N[Not[LessEqual[phi2, 0.000105]], $MachinePrecision]], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[t$95$0], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$1 + 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[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$1 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[(N[Cos[N[(2.0 * t$95$0), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \left(\lambda_1 - \lambda_2\right) \cdot 0.5\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -2.05 \cdot 10^{-5} \lor \neg \left(\phi_2 \leq 0.000105\right):\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {\sin t\_0}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_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{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_2 \cdot \left(t\_1 \cdot t\_2\right)}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot \left(\frac{\cos \left(2 \cdot t\_0\right)}{2} - 0.5\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -2.05000000000000002e-5 or 1.05e-4 < phi2 Initial program 43.8%
Simplified43.8%
Applied egg-rr23.5%
unpow123.5%
Simplified23.5%
Taylor expanded in phi1 around 0 45.2%
if -2.05000000000000002e-5 < phi2 < 1.05e-4Initial program 83.2%
Taylor expanded in phi1 around inf 83.2%
expm1-log1p-u83.2%
associate--r+83.2%
unpow283.2%
1-sub-sin83.3%
pow283.3%
div-inv83.3%
metadata-eval83.3%
associate-*r*83.3%
associate-*l*83.3%
pow283.3%
Applied egg-rr83.3%
associate-*r*83.3%
*-commutative83.3%
Simplified83.3%
Taylor expanded in phi2 around 0 83.3%
*-commutative83.3%
Simplified83.3%
*-commutative83.3%
metadata-eval83.3%
div-inv83.3%
pow283.3%
sin-mult83.4%
div-inv83.4%
metadata-eval83.4%
div-inv83.4%
metadata-eval83.4%
cos-sum83.3%
cos-283.4%
div-inv83.4%
metadata-eval83.4%
Applied egg-rr83.4%
div-sub83.4%
+-inverses83.4%
cos-083.4%
metadata-eval83.4%
*-commutative83.4%
Simplified83.4%
Final simplification63.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5)))
(t_1 (* (cos phi1) (pow t_0 2.0)))
(t_2 (* (cos phi1) (cos phi2))))
(if (or (<= phi1 -5.2e-24) (not (<= phi1 1.85e-50)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) t_1)))))
(*
(* 2.0 R)
(atan2
(hypot (sin (* 0.5 (- phi1 phi2))) (* t_0 (sqrt t_2)))
(sqrt
(-
1.0
(fma
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
t_2
(pow (sin (* phi2 -0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
double t_1 = cos(phi1) * pow(t_0, 2.0);
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if ((phi1 <= -5.2e-24) || !(phi1 <= 1.85e-50)) {
tmp = R * (2.0 * atan2(sqrt((t_1 + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - t_1))));
} else {
tmp = (2.0 * R) * atan2(hypot(sin((0.5 * (phi1 - phi2))), (t_0 * sqrt(t_2))), sqrt((1.0 - fma((0.5 - (0.5 * cos((lambda1 - lambda2)))), t_2, 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)) t_1 = Float64(cos(phi1) * (t_0 ^ 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi1 <= -5.2e-24) || !(phi1 <= 1.85e-50)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - t_1))))); else tmp = Float64(Float64(2.0 * R) * atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(t_0 * sqrt(t_2))), sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), t_2, (sin(Float64(phi2 * -0.5)) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi1, -5.2e-24], N[Not[LessEqual[phi1, 1.85e-50]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$0 * N[Sqrt[t$95$2], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$2 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
t_1 := \cos \phi_1 \cdot {t\_0}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_1 \leq -5.2 \cdot 10^{-24} \lor \neg \left(\phi_1 \leq 1.85 \cdot 10^{-50}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), t\_0 \cdot \sqrt{t\_2}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi1 < -5.2e-24 or 1.85e-50 < phi1 Initial program 50.4%
Taylor expanded in phi1 around inf 46.7%
expm1-log1p-u46.7%
associate--r+46.7%
unpow246.7%
1-sub-sin46.8%
pow246.8%
div-inv46.8%
metadata-eval46.8%
associate-*r*46.8%
associate-*l*46.8%
pow246.8%
Applied egg-rr46.8%
associate-*r*46.8%
*-commutative46.8%
Simplified46.8%
Taylor expanded in phi2 around 0 47.6%
*-commutative47.6%
Simplified47.6%
Taylor expanded in phi2 around 0 48.2%
if -5.2e-24 < phi1 < 1.85e-50Initial program 79.3%
Simplified79.2%
Applied egg-rr66.5%
unpow166.5%
Simplified66.5%
Taylor expanded in phi1 around 0 66.5%
*-commutative66.5%
Simplified66.5%
Final simplification55.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(sqrt
(+
(pow (cos (* phi1 0.5)) 2.0)
(*
(cos phi1)
(- (/ (cos (* 2.0 (* (- lambda1 lambda2) 0.5))) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt((pow(cos((phi1 * 0.5)), 2.0) + (cos(phi1) * ((cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) + (cos(phi1) * ((cos((2.0d0 * ((lambda1 - lambda2) * 0.5d0))) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) + (Math.cos(phi1) * ((Math.cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) + (math.cos(phi1) * ((math.cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * Float64(Float64(cos(Float64(2.0 * Float64(Float64(lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) + (cos(phi1) * ((cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[(N[Cos[N[(2.0 * N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot \left(\frac{\cos \left(2 \cdot \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.6%
Taylor expanded in phi1 around inf 49.8%
expm1-log1p-u49.8%
associate--r+49.8%
unpow249.8%
1-sub-sin49.8%
pow249.8%
div-inv49.8%
metadata-eval49.8%
associate-*r*49.8%
associate-*l*49.8%
pow249.8%
Applied egg-rr49.8%
associate-*r*49.8%
*-commutative49.8%
Simplified49.8%
Taylor expanded in phi2 around 0 50.4%
*-commutative50.4%
Simplified50.4%
*-commutative50.4%
metadata-eval50.4%
div-inv50.4%
pow250.4%
sin-mult50.4%
div-inv50.4%
metadata-eval50.4%
div-inv50.4%
metadata-eval50.4%
cos-sum50.4%
cos-250.4%
div-inv50.4%
metadata-eval50.4%
Applied egg-rr50.4%
div-sub50.4%
+-inverses50.4%
cos-050.4%
metadata-eval50.4%
*-commutative50.4%
Simplified50.4%
Final simplification50.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt((t_0 + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - t_0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = cos(phi1) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)
code = r * (2.0d0 * atan2(sqrt((t_0 + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - t_0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((t_0 + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - t_0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) return R * (2.0 * math.atan2(math.sqrt((t_0 + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - t_0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - t_0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0); tmp = R * (2.0 * atan2(sqrt((t_0 + (sin((phi1 * 0.5)) ^ 2.0))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - t_0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.6%
Taylor expanded in phi1 around inf 49.8%
expm1-log1p-u49.8%
associate--r+49.8%
unpow249.8%
1-sub-sin49.8%
pow249.8%
div-inv49.8%
metadata-eval49.8%
associate-*r*49.8%
associate-*l*49.8%
pow249.8%
Applied egg-rr49.8%
associate-*r*49.8%
*-commutative49.8%
Simplified49.8%
Taylor expanded in phi2 around 0 50.4%
*-commutative50.4%
Simplified50.4%
Taylor expanded in phi2 around 0 48.6%
Final simplification48.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (cos phi1) t_0)))
(sqrt (- 1.0 (* (cos phi2) t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (cos(phi1) * t_0))), sqrt((1.0 - (cos(phi2) * t_0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (cos(phi1) * t_0))), sqrt((1.0d0 - (cos(phi2) * t_0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (Math.cos(phi1) * t_0))), Math.sqrt((1.0 - (Math.cos(phi2) * t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (math.cos(phi1) * t_0))), math.sqrt((1.0 - (math.cos(phi2) * t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(cos(phi1) * t_0))), sqrt(Float64(1.0 - Float64(cos(phi2) * t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (cos(phi1) * t_0))), sqrt((1.0 - (cos(phi2) * t_0))))); 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]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \cos \phi_1 \cdot t\_0}}{\sqrt{1 - \cos \phi_2 \cdot t\_0}}\right)
\end{array}
\end{array}
Initial program 62.6%
Taylor expanded in phi1 around inf 49.8%
Taylor expanded in phi1 around 0 35.6%
Taylor expanded in phi2 around 0 36.2%
Final simplification36.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt((t_0 + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - t_0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)
code = r * (2.0d0 * atan2(sqrt((t_0 + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt((1.0d0 - t_0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.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((phi2 * -0.5)), 2.0))), Math.sqrt((1.0 - t_0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = 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((phi2 * -0.5)), 2.0))), math.sqrt((1.0 - t_0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = 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(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - t_0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0); tmp = R * (2.0 * atan2(sqrt((t_0 + (sin((phi2 * -0.5)) ^ 2.0))), sqrt((1.0 - t_0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.6%
Taylor expanded in phi1 around inf 49.8%
Taylor expanded in phi1 around 0 35.6%
Taylor expanded in phi1 around 0 34.4%
Final simplification34.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (- lambda1 lambda2) 0.5)))
(*
R
(*
2.0
(atan2
(sqrt
(+ (* (cos phi1) (pow (sin t_0) 2.0)) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (+ 1.0 (* (cos phi2) (- (/ (cos (* 2.0 t_0)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (lambda1 - lambda2) * 0.5;
return R * (2.0 * atan2(sqrt(((cos(phi1) * pow(sin(t_0), 2.0)) + pow(sin((phi1 * 0.5)), 2.0))), sqrt((1.0 + (cos(phi2) * ((cos((2.0 * t_0)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = (lambda1 - lambda2) * 0.5d0
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (sin(t_0) ** 2.0d0)) + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt((1.0d0 + (cos(phi2) * ((cos((2.0d0 * t_0)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (lambda1 - lambda2) * 0.5;
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * Math.pow(Math.sin(t_0), 2.0)) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((1.0 + (Math.cos(phi2) * ((Math.cos((2.0 * t_0)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = (lambda1 - lambda2) * 0.5 return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * math.pow(math.sin(t_0), 2.0)) + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((1.0 + (math.cos(phi2) * ((math.cos((2.0 * t_0)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(lambda1 - lambda2) * 0.5) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * (sin(t_0) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 + Float64(cos(phi2) * Float64(Float64(cos(Float64(2.0 * t_0)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = (lambda1 - lambda2) * 0.5; tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (sin(t_0) ^ 2.0)) + (sin((phi1 * 0.5)) ^ 2.0))), sqrt((1.0 + (cos(phi2) * ((cos((2.0 * t_0)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[t$95$0], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(2.0 * t$95$0), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \left(\lambda_1 - \lambda_2\right) \cdot 0.5\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin t\_0}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{1 + \cos \phi_2 \cdot \left(\frac{\cos \left(2 \cdot t\_0\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 62.6%
Taylor expanded in phi1 around inf 49.8%
Taylor expanded in phi1 around 0 35.6%
Taylor expanded in phi2 around 0 34.1%
*-commutative50.4%
metadata-eval50.4%
div-inv50.4%
pow250.4%
sin-mult50.4%
div-inv50.4%
metadata-eval50.4%
div-inv50.4%
metadata-eval50.4%
cos-sum50.4%
cos-250.4%
div-inv50.4%
metadata-eval50.4%
Applied egg-rr34.2%
div-sub50.4%
+-inverses50.4%
cos-050.4%
metadata-eval50.4%
*-commutative50.4%
Simplified34.2%
Final simplification34.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt(((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))), sqrt((1.0 - t_0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * t_0) + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt((1.0d0 - t_0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * t_0) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((1.0 - t_0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * t_0) + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((1.0 - t_0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - t_0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_0) + (sin((phi1 * 0.5)) ^ 2.0))), sqrt((1.0 - t_0)))); 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]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[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] / N[Sqrt[N[(1.0 - t$95$0), $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}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.6%
Taylor expanded in phi1 around inf 49.8%
Taylor expanded in phi1 around 0 35.6%
Taylor expanded in phi2 around 0 34.1%
Taylor expanded in phi2 around 0 34.1%
Final simplification34.1%
(FPCore (R lambda1 lambda2 phi1 phi2) :precision binary64 (let* ((t_0 (sin (* (- lambda1 lambda2) 0.5)))) (* R (* 2.0 (atan2 t_0 (sqrt (- 1.0 (* (cos phi2) (pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
return R * (2.0 * atan2(t_0, sqrt((1.0 - (cos(phi2) * pow(t_0, 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) * 0.5d0))
code = r * (2.0d0 * atan2(t_0, sqrt((1.0d0 - (cos(phi2) * (t_0 ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) * 0.5));
return R * (2.0 * Math.atan2(t_0, Math.sqrt((1.0 - (Math.cos(phi2) * Math.pow(t_0, 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) * 0.5)) return R * (2.0 * math.atan2(t_0, math.sqrt((1.0 - (math.cos(phi2) * math.pow(t_0, 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) return Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - Float64(cos(phi2) * (t_0 ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)); tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - (cos(phi2) * (t_0 ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $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(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \cos \phi_2 \cdot {t\_0}^{2}}}\right)
\end{array}
\end{array}
Initial program 62.6%
Taylor expanded in phi1 around inf 49.8%
Taylor expanded in phi1 around 0 35.6%
Taylor expanded in phi2 around 0 34.1%
Taylor expanded in phi1 around 0 18.3%
Final simplification18.3%
herbie shell --seed 2024157
(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))))))))))