
(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 (cos (* 0.5 phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (cos (* 0.5 phi1)))
(t_3 (sin (* 0.5 phi2)))
(t_4 (* (cos phi1) (cos phi2)))
(t_5 (sin (* 0.5 phi1))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma t_5 t_0 (* t_2 (- t_3))) 2.0)
(* (* t_4 (log1p (expm1 (sin (* 0.5 (- lambda1 lambda2)))))) t_1)))
(sqrt
(-
1.0
(+ (* t_1 (* t_4 t_1)) (pow (- (* t_5 t_0) (* t_2 t_3)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi2));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos((0.5 * phi1));
double t_3 = sin((0.5 * phi2));
double t_4 = cos(phi1) * cos(phi2);
double t_5 = sin((0.5 * phi1));
return R * (2.0 * atan2(sqrt((pow(fma(t_5, t_0, (t_2 * -t_3)), 2.0) + ((t_4 * log1p(expm1(sin((0.5 * (lambda1 - lambda2)))))) * t_1))), sqrt((1.0 - ((t_1 * (t_4 * t_1)) + pow(((t_5 * t_0) - (t_2 * t_3)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(0.5 * phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = cos(Float64(0.5 * phi1)) t_3 = sin(Float64(0.5 * phi2)) t_4 = Float64(cos(phi1) * cos(phi2)) t_5 = sin(Float64(0.5 * phi1)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_5, t_0, Float64(t_2 * Float64(-t_3))) ^ 2.0) + Float64(Float64(t_4 * log1p(expm1(sin(Float64(0.5 * Float64(lambda1 - lambda2)))))) * t_1))), sqrt(Float64(1.0 - Float64(Float64(t_1 * Float64(t_4 * t_1)) + (Float64(Float64(t_5 * t_0) - Float64(t_2 * t_3)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$5 * t$95$0 + N[(t$95$2 * (-t$95$3)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$4 * N[Log[1 + N[(Exp[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]] - 1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$1 * N[(t$95$4 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(t$95$5 * t$95$0), $MachinePrecision] - N[(t$95$2 * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_2\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \left(0.5 \cdot \phi_1\right)\\
t_3 := \sin \left(0.5 \cdot \phi_2\right)\\
t_4 := \cos \phi_1 \cdot \cos \phi_2\\
t_5 := \sin \left(0.5 \cdot \phi_1\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_5, t\_0, t\_2 \cdot \left(-t\_3\right)\right)\right)}^{2} + \left(t\_4 \cdot \mathsf{log1p}\left(\mathsf{expm1}\left(\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right)\right)\right) \cdot t\_1}}{\sqrt{1 - \left(t\_1 \cdot \left(t\_4 \cdot t\_1\right) + {\left(t\_5 \cdot t\_0 - t\_2 \cdot t\_3\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.5%
div-sub65.5%
sin-diff66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
Applied egg-rr66.6%
div-sub65.5%
sin-diff66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
Applied egg-rr78.0%
fma-neg78.0%
*-commutative78.0%
*-commutative78.0%
*-commutative78.0%
*-commutative78.0%
*-commutative78.0%
distribute-rgt-neg-in78.0%
Simplified78.0%
add-sqr-sqrt34.6%
sqrt-prod51.6%
log1p-expm1-u51.6%
sqrt-prod34.6%
add-sqr-sqrt78.0%
div-inv78.0%
metadata-eval78.0%
Applied egg-rr78.0%
Final simplification78.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* 0.5 phi2)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_2 (* (* (cos phi1) (cos phi2)) t_2)))
(t_4 (sin (* 0.5 phi1))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_4 t_0 (* t_1 (- (sin (* 0.5 phi2))))) 2.0) t_3))
(sqrt
(-
1.0
(+ t_3 (pow (fma t_0 t_4 (* t_1 (sin (* phi2 -0.5)))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi2));
double t_1 = cos((0.5 * phi1));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * ((cos(phi1) * cos(phi2)) * t_2);
double t_4 = sin((0.5 * phi1));
return R * (2.0 * atan2(sqrt((pow(fma(t_4, t_0, (t_1 * -sin((0.5 * phi2)))), 2.0) + t_3)), sqrt((1.0 - (t_3 + pow(fma(t_0, t_4, (t_1 * sin((phi2 * -0.5)))), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(0.5 * phi2)) t_1 = cos(Float64(0.5 * phi1)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_2 * Float64(Float64(cos(phi1) * cos(phi2)) * t_2)) t_4 = sin(Float64(0.5 * phi1)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_4, t_0, Float64(t_1 * Float64(-sin(Float64(0.5 * phi2))))) ^ 2.0) + t_3)), sqrt(Float64(1.0 - Float64(t_3 + (fma(t_0, t_4, Float64(t_1 * sin(Float64(phi2 * -0.5)))) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$4 * t$95$0 + N[(t$95$1 * (-N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision])), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 + N[Power[N[(t$95$0 * t$95$4 + N[(t$95$1 * N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_2\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_2 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2\right)\\
t_4 := \sin \left(0.5 \cdot \phi_1\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_4, t\_0, t\_1 \cdot \left(-\sin \left(0.5 \cdot \phi_2\right)\right)\right)\right)}^{2} + t\_3}}{\sqrt{1 - \left(t\_3 + {\left(\mathsf{fma}\left(t\_0, t\_4, t\_1 \cdot \sin \left(\phi_2 \cdot -0.5\right)\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.5%
div-sub65.5%
sin-diff66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
Applied egg-rr66.6%
div-sub65.5%
sin-diff66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
Applied egg-rr78.0%
fma-neg78.0%
*-commutative78.0%
*-commutative78.0%
*-commutative78.0%
*-commutative78.0%
*-commutative78.0%
distribute-rgt-neg-in78.0%
Simplified78.0%
Taylor expanded in phi1 around inf 78.0%
fma-neg78.0%
*-commutative78.0%
*-commutative78.0%
distribute-lft-neg-in78.0%
sin-neg78.0%
distribute-lft-neg-in78.0%
metadata-eval78.0%
*-commutative78.0%
*-commutative78.0%
Simplified78.0%
Final simplification78.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* 0.5 phi2)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (sin (* 0.5 phi2)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* t_3 (* (* (cos phi1) (cos phi2)) t_3)))
(t_5 (sin (* 0.5 phi1))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_5 t_0 (* t_1 (- t_2))) 2.0) t_4))
(sqrt (- 1.0 (+ t_4 (pow (- (* t_5 t_0) (* t_1 t_2)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi2));
double t_1 = cos((0.5 * phi1));
double t_2 = sin((0.5 * phi2));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = t_3 * ((cos(phi1) * cos(phi2)) * t_3);
double t_5 = sin((0.5 * phi1));
return R * (2.0 * atan2(sqrt((pow(fma(t_5, t_0, (t_1 * -t_2)), 2.0) + t_4)), sqrt((1.0 - (t_4 + pow(((t_5 * t_0) - (t_1 * t_2)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(0.5 * phi2)) t_1 = cos(Float64(0.5 * phi1)) t_2 = sin(Float64(0.5 * phi2)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(t_3 * Float64(Float64(cos(phi1) * cos(phi2)) * t_3)) t_5 = sin(Float64(0.5 * phi1)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_5, t_0, Float64(t_1 * Float64(-t_2))) ^ 2.0) + t_4)), sqrt(Float64(1.0 - Float64(t_4 + (Float64(Float64(t_5 * t_0) - Float64(t_1 * t_2)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$3 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$5 * t$95$0 + N[(t$95$1 * (-t$95$2)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$4 + N[Power[N[(N[(t$95$5 * t$95$0), $MachinePrecision] - N[(t$95$1 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_2\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \sin \left(0.5 \cdot \phi_2\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := t\_3 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_3\right)\\
t_5 := \sin \left(0.5 \cdot \phi_1\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_5, t\_0, t\_1 \cdot \left(-t\_2\right)\right)\right)}^{2} + t\_4}}{\sqrt{1 - \left(t\_4 + {\left(t\_5 \cdot t\_0 - t\_1 \cdot t\_2\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.5%
div-sub65.5%
sin-diff66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
Applied egg-rr66.6%
div-sub65.5%
sin-diff66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
Applied egg-rr78.0%
fma-neg78.0%
*-commutative78.0%
*-commutative78.0%
*-commutative78.0%
*-commutative78.0%
*-commutative78.0%
distribute-rgt-neg-in78.0%
Simplified78.0%
Final simplification78.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(pow
(-
(* (sin (* 0.5 phi1)) (cos (* 0.5 phi2)))
(* (cos (* 0.5 phi1)) (sin (* 0.5 phi2))))
2.0))
(t_2 (* (* (cos phi1) (cos phi2)) t_0))
(t_3 (* t_0 t_2))
(t_4 (+ t_3 t_1)))
(if (or (<= lambda1 -1.4) (not (<= lambda1 3e-18)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_3 (- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt (- 1.0 t_4)))))
(*
R
(*
2.0
(atan2
(sqrt t_4)
(sqrt (- 1.0 (+ t_1 (* t_2 (sin (* lambda2 -0.5))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(((sin((0.5 * phi1)) * cos((0.5 * phi2))) - (cos((0.5 * phi1)) * sin((0.5 * phi2)))), 2.0);
double t_2 = (cos(phi1) * cos(phi2)) * t_0;
double t_3 = t_0 * t_2;
double t_4 = t_3 + t_1;
double tmp;
if ((lambda1 <= -1.4) || !(lambda1 <= 3e-18)) {
tmp = R * (2.0 * atan2(sqrt((t_3 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - t_4))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_4), sqrt((1.0 - (t_1 + (t_2 * sin((lambda2 * -0.5))))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = ((sin((0.5d0 * phi1)) * cos((0.5d0 * phi2))) - (cos((0.5d0 * phi1)) * sin((0.5d0 * phi2)))) ** 2.0d0
t_2 = (cos(phi1) * cos(phi2)) * t_0
t_3 = t_0 * t_2
t_4 = t_3 + t_1
if ((lambda1 <= (-1.4d0)) .or. (.not. (lambda1 <= 3d-18))) then
tmp = r * (2.0d0 * atan2(sqrt((t_3 + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt((1.0d0 - t_4))))
else
tmp = r * (2.0d0 * atan2(sqrt(t_4), sqrt((1.0d0 - (t_1 + (t_2 * sin((lambda2 * (-0.5d0)))))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(((Math.sin((0.5 * phi1)) * Math.cos((0.5 * phi2))) - (Math.cos((0.5 * phi1)) * Math.sin((0.5 * phi2)))), 2.0);
double t_2 = (Math.cos(phi1) * Math.cos(phi2)) * t_0;
double t_3 = t_0 * t_2;
double t_4 = t_3 + t_1;
double tmp;
if ((lambda1 <= -1.4) || !(lambda1 <= 3e-18)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((1.0 - t_4))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(t_4), Math.sqrt((1.0 - (t_1 + (t_2 * Math.sin((lambda2 * -0.5))))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(((math.sin((0.5 * phi1)) * math.cos((0.5 * phi2))) - (math.cos((0.5 * phi1)) * math.sin((0.5 * phi2)))), 2.0) t_2 = (math.cos(phi1) * math.cos(phi2)) * t_0 t_3 = t_0 * t_2 t_4 = t_3 + t_1 tmp = 0 if (lambda1 <= -1.4) or not (lambda1 <= 3e-18): tmp = R * (2.0 * math.atan2(math.sqrt((t_3 + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt((1.0 - t_4)))) else: tmp = R * (2.0 * math.atan2(math.sqrt(t_4), math.sqrt((1.0 - (t_1 + (t_2 * math.sin((lambda2 * -0.5)))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(sin(Float64(0.5 * phi1)) * cos(Float64(0.5 * phi2))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(0.5 * phi2)))) ^ 2.0 t_2 = Float64(Float64(cos(phi1) * cos(phi2)) * t_0) t_3 = Float64(t_0 * t_2) t_4 = Float64(t_3 + t_1) tmp = 0.0 if ((lambda1 <= -1.4) || !(lambda1 <= 3e-18)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(1.0 - t_4))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_4), sqrt(Float64(1.0 - Float64(t_1 + Float64(t_2 * sin(Float64(lambda2 * -0.5))))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = ((sin((0.5 * phi1)) * cos((0.5 * phi2))) - (cos((0.5 * phi1)) * sin((0.5 * phi2)))) ^ 2.0; t_2 = (cos(phi1) * cos(phi2)) * t_0; t_3 = t_0 * t_2; t_4 = t_3 + t_1; tmp = 0.0; if ((lambda1 <= -1.4) || ~((lambda1 <= 3e-18))) tmp = R * (2.0 * atan2(sqrt((t_3 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - t_4)))); else tmp = R * (2.0 * atan2(sqrt(t_4), sqrt((1.0 - (t_1 + (t_2 * sin((lambda2 * -0.5)))))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[(N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$3 = N[(t$95$0 * t$95$2), $MachinePrecision]}, Block[{t$95$4 = N[(t$95$3 + t$95$1), $MachinePrecision]}, If[Or[LessEqual[lambda1, -1.4], N[Not[LessEqual[lambda1, 3e-18]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$4], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[(t$95$2 * N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\left(\sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(0.5 \cdot \phi_2\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\\
t_2 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\\
t_3 := t\_0 \cdot t\_2\\
t_4 := t\_3 + t\_1\\
\mathbf{if}\;\lambda_1 \leq -1.4 \lor \neg \left(\lambda_1 \leq 3 \cdot 10^{-18}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{1 - t\_4}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4}}{\sqrt{1 - \left(t\_1 + t\_2 \cdot \sin \left(\lambda_2 \cdot -0.5\right)\right)}}\right)\\
\end{array}
\end{array}
if lambda1 < -1.3999999999999999 or 2.99999999999999983e-18 < lambda1 Initial program 50.1%
div-sub50.1%
sin-diff51.6%
div-inv51.6%
metadata-eval51.6%
div-inv51.6%
metadata-eval51.6%
div-inv51.6%
metadata-eval51.6%
div-inv51.6%
metadata-eval51.6%
Applied egg-rr51.6%
unpow238.2%
sin-mult38.2%
div-inv38.2%
metadata-eval38.2%
div-inv38.2%
metadata-eval38.2%
div-inv38.2%
metadata-eval38.2%
div-inv38.2%
metadata-eval38.2%
Applied egg-rr51.6%
div-sub38.2%
+-inverses38.2%
cos-038.2%
metadata-eval38.2%
distribute-lft-out38.2%
metadata-eval38.2%
*-rgt-identity38.2%
Simplified51.6%
if -1.3999999999999999 < lambda1 < 2.99999999999999983e-18Initial program 82.1%
div-sub82.1%
sin-diff82.9%
div-inv82.9%
metadata-eval82.9%
div-inv82.9%
metadata-eval82.9%
div-inv82.9%
metadata-eval82.9%
div-inv82.9%
metadata-eval82.9%
Applied egg-rr82.9%
Taylor expanded in lambda1 around 0 82.9%
div-sub82.1%
sin-diff82.9%
div-inv82.9%
metadata-eval82.9%
div-inv82.9%
metadata-eval82.9%
div-inv82.9%
metadata-eval82.9%
div-inv82.9%
metadata-eval82.9%
Applied egg-rr97.6%
Final simplification73.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow
(-
(* (sin (* 0.5 phi1)) (cos (* 0.5 phi2)))
(* (cos (* 0.5 phi1)) (sin (* 0.5 phi2))))
2.0))))
(* 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 = (t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(((sin((0.5 * phi1)) * cos((0.5 * phi2))) - (cos((0.5 * phi1)) * sin((0.5 * phi2)))), 2.0);
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 = (t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (((sin((0.5d0 * phi1)) * cos((0.5d0 * phi2))) - (cos((0.5d0 * phi1)) * sin((0.5d0 * phi2)))) ** 2.0d0)
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 = (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(((Math.sin((0.5 * phi1)) * Math.cos((0.5 * phi2))) - (Math.cos((0.5 * phi1)) * Math.sin((0.5 * phi2)))), 2.0);
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 = (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(((math.sin((0.5 * phi1)) * math.cos((0.5 * phi2))) - (math.cos((0.5 * phi1)) * math.sin((0.5 * phi2)))), 2.0) 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(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (Float64(Float64(sin(Float64(0.5 * phi1)) * cos(Float64(0.5 * phi2))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(0.5 * phi2)))) ^ 2.0)) 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 = (t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (((sin((0.5 * phi1)) * cos((0.5 * phi2))) - (cos((0.5 * phi1)) * sin((0.5 * phi2)))) ^ 2.0); 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[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $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 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\left(\sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(0.5 \cdot \phi_2\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Initial program 65.5%
div-sub65.5%
sin-diff66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
Applied egg-rr66.6%
div-sub65.5%
sin-diff66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
Applied egg-rr78.0%
Final simplification78.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt
(-
(-
1.0
(pow
(-
(* (sin (* 0.5 phi1)) (cos (* 0.5 phi2)))
(* (cos (* 0.5 phi1)) (sin (* 0.5 phi2))))
2.0))
t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt(((1.0 - pow(((sin((0.5 * phi1)) * cos((0.5 * phi2))) - (cos((0.5 * phi1)) * sin((0.5 * phi2)))), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt(((1.0d0 - (((sin((0.5d0 * phi1)) * cos((0.5d0 * phi2))) - (cos((0.5d0 * phi1)) * sin((0.5d0 * phi2)))) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt(((1.0 - Math.pow(((Math.sin((0.5 * phi1)) * Math.cos((0.5 * phi2))) - (Math.cos((0.5 * phi1)) * Math.sin((0.5 * phi2)))), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt(((1.0 - math.pow(((math.sin((0.5 * phi1)) * math.cos((0.5 * phi2))) - (math.cos((0.5 * phi1)) * math.sin((0.5 * phi2)))), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(Float64(1.0 - (Float64(Float64(sin(Float64(0.5 * phi1)) * cos(Float64(0.5 * phi2))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(0.5 * phi2)))) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(((1.0 - (((sin((0.5 * phi1)) * cos((0.5 * phi2))) - (cos((0.5 * phi1)) * sin((0.5 * phi2)))) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[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[Power[N[(N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{\left(1 - {\left(\sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(0.5 \cdot \phi_2\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 65.5%
associate-*l*65.5%
Simplified65.5%
div-sub65.5%
sin-diff66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
Applied egg-rr66.6%
Final simplification66.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(+
t_1
(pow
(-
(* (sin (* 0.5 phi1)) (cos (* 0.5 phi2)))
(* (cos (* 0.5 phi1)) (sin (* 0.5 phi2))))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (t_1 + pow(((sin((0.5 * phi1)) * cos((0.5 * phi2))) - (cos((0.5 * phi1)) * sin((0.5 * 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
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (t_1 + (((sin((0.5d0 * phi1)) * cos((0.5d0 * phi2))) - (cos((0.5d0 * phi1)) * sin((0.5d0 * phi2)))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - (t_1 + Math.pow(((Math.sin((0.5 * phi1)) * Math.cos((0.5 * phi2))) - (Math.cos((0.5 * phi1)) * Math.sin((0.5 * phi2)))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - (t_1 + math.pow(((math.sin((0.5 * phi1)) * math.cos((0.5 * phi2))) - (math.cos((0.5 * phi1)) * math.sin((0.5 * phi2)))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_1 + (Float64(Float64(sin(Float64(0.5 * phi1)) * cos(Float64(0.5 * phi2))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(0.5 * phi2)))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (t_1 + (((sin((0.5 * phi1)) * cos((0.5 * phi2))) - (cos((0.5 * phi1)) * sin((0.5 * 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[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[(N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \left(t\_1 + {\left(\sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(0.5 \cdot \phi_2\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 65.5%
div-sub65.5%
sin-diff66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
div-inv66.6%
metadata-eval66.6%
Applied egg-rr66.6%
Final simplification66.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= t_0 -0.0001) (not (<= t_0 5e-12)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* 0.5 phi1)) 2.0)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt
(-
(pow (cos (* 0.5 phi1)) 2.0)
(* (cos phi1) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((t_0 <= -0.0001) || !(t_0 <= 5e-12)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((0.5 * phi1)), 2.0) + (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt((pow(cos((0.5 * phi1)), 2.0) - (cos(phi1) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
if ((t_0 <= (-0.0001d0)) .or. (.not. (t_0 <= 5d-12))) then
tmp = r * (2.0d0 * atan2(sqrt(((sin((0.5d0 * phi1)) ** 2.0d0) + (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))), sqrt(((cos((0.5d0 * phi1)) ** 2.0d0) - (cos(phi1) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((t_0 <= -0.0001) || !(t_0 <= 5e-12)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((0.5 * phi1)), 2.0) + (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), Math.sqrt((Math.pow(Math.cos((0.5 * phi1)), 2.0) - (Math.cos(phi1) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (t_0 <= -0.0001) or not (t_0 <= 5e-12): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((0.5 * phi1)), 2.0) + (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), math.sqrt((math.pow(math.cos((0.5 * phi1)), 2.0) - (math.cos(phi1) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((t_0 <= -0.0001) || !(t_0 <= 5e-12)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(0.5 * phi1)) ^ 2.0) + Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - Float64(cos(phi1) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((t_0 <= -0.0001) || ~((t_0 <= 5e-12))) tmp = R * (2.0 * atan2(sqrt(((sin((0.5 * phi1)) ^ 2.0) + (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))), sqrt(((cos((0.5 * phi1)) ^ 2.0) - (cos(phi1) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[t$95$0, -0.0001], N[Not[LessEqual[t$95$0, 5e-12]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;t\_0 \leq -0.0001 \lor \neg \left(t\_0 \leq 5 \cdot 10^{-12}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(0.5 \cdot \phi_1\right)}^{2} + \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}{\sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - \cos \phi_1 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) < -1.00000000000000005e-4 or 4.9999999999999997e-12 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) Initial program 59.7%
Taylor expanded in phi2 around 0 46.9%
Taylor expanded in phi2 around 0 47.6%
+-commutative7.6%
associate--r+7.6%
unpow27.6%
1-sub-sin7.6%
unpow27.6%
sub-neg7.6%
mul-1-neg7.6%
distribute-lft-in7.6%
metadata-eval7.6%
associate-*r*7.6%
associate-*r*7.6%
metadata-eval7.6%
distribute-lft-in7.6%
+-commutative7.6%
Simplified47.6%
Taylor expanded in phi2 around 0 48.6%
if -1.00000000000000005e-4 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) < 4.9999999999999997e-12Initial program 83.3%
Taylor expanded in lambda1 around 0 83.3%
Taylor expanded in lambda2 around 0 82.6%
Final simplification57.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (+ 1.0 (- (- (/ (cos (- phi1 phi2)) 2.0) 0.5) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 + (((cos((phi1 - phi2)) / 2.0d0) - 0.5d0) - t_1)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 + (((Math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 + (((math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 + Float64(Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5) - t_1)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision] - t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 + \left(\left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right) - t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 65.5%
unpow251.6%
sin-mult49.4%
div-inv49.4%
metadata-eval49.4%
div-inv49.4%
metadata-eval49.4%
div-inv49.4%
metadata-eval49.4%
div-inv49.4%
metadata-eval49.4%
Applied egg-rr65.6%
div-sub49.4%
+-inverses49.4%
cos-049.4%
metadata-eval49.4%
distribute-lft-out49.4%
metadata-eval49.4%
*-rgt-identity49.4%
Simplified65.6%
Final simplification65.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (pow (sin (* 0.5 phi1)) 2.0))
(t_3 (sqrt (- (pow (cos (* 0.5 phi1)) 2.0) (* (cos phi1) t_0))))
(t_4 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= phi1 -0.056)
(* R (* 2.0 (atan2 (sqrt (fma (cos phi1) t_1 t_2)) t_3)))
(if (<= phi1 5.1e-6)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_4 (* (* (cos phi1) (cos phi2)) t_4))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0))))))
(* R (* 2.0 (atan2 (sqrt (+ t_2 (* (cos phi1) t_1))) t_3)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = pow(sin((0.5 * phi1)), 2.0);
double t_3 = sqrt((pow(cos((0.5 * phi1)), 2.0) - (cos(phi1) * t_0)));
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi1 <= -0.056) {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi1), t_1, t_2)), t_3));
} else if (phi1 <= 5.1e-6) {
tmp = R * (2.0 * atan2(sqrt(((t_4 * ((cos(phi1) * cos(phi2)) * t_4)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_2 + (cos(phi1) * t_1))), t_3));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = sin(Float64(0.5 * phi1)) ^ 2.0 t_3 = sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - Float64(cos(phi1) * t_0))) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (phi1 <= -0.056) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), t_1, t_2)), t_3))); elseif (phi1 <= 5.1e-6) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_4 * Float64(Float64(cos(phi1) * cos(phi2)) * t_4)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(cos(phi1) * t_1))), t_3))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -0.056], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * t$95$1 + t$95$2), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 5.1e-6], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$4 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := {\sin \left(0.5 \cdot \phi_1\right)}^{2}\\
t_3 := \sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - \cos \phi_1 \cdot t\_0}\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_1 \leq -0.056:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, t\_1, t\_2\right)}}{t\_3}\right)\\
\mathbf{elif}\;\phi_1 \leq 5.1 \cdot 10^{-6}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_4\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + \cos \phi_1 \cdot t\_1}}{t\_3}\right)\\
\end{array}
\end{array}
if phi1 < -0.0560000000000000012Initial program 54.7%
Taylor expanded in phi2 around 0 54.4%
Taylor expanded in phi2 around 0 55.5%
+-commutative7.9%
associate--r+7.9%
unpow27.9%
1-sub-sin7.9%
unpow27.9%
sub-neg7.9%
mul-1-neg7.9%
distribute-lft-in7.9%
metadata-eval7.9%
associate-*r*7.9%
associate-*r*7.9%
metadata-eval7.9%
distribute-lft-in7.9%
+-commutative7.9%
Simplified55.6%
Taylor expanded in phi2 around 0 56.6%
fma-def56.6%
Simplified56.6%
if -0.0560000000000000012 < phi1 < 5.1000000000000003e-6Initial program 78.7%
Taylor expanded in phi1 around 0 78.7%
Simplified78.8%
if 5.1000000000000003e-6 < phi1 Initial program 47.3%
Taylor expanded in phi2 around 0 47.6%
Taylor expanded in phi2 around 0 48.5%
+-commutative7.9%
associate--r+7.9%
unpow27.9%
1-sub-sin7.9%
unpow27.9%
sub-neg7.9%
mul-1-neg7.9%
distribute-lft-in7.9%
metadata-eval7.9%
associate-*r*7.9%
associate-*r*7.9%
metadata-eval7.9%
distribute-lft-in7.9%
+-commutative7.9%
Simplified48.6%
Taylor expanded in phi2 around 0 49.0%
Final simplification66.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (pow (sin (* 0.5 phi1)) 2.0))
(t_3 (sqrt (- (pow (cos (* 0.5 phi1)) 2.0) (* (cos phi1) t_0))))
(t_4 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= phi1 -0.056)
(* R (* 2.0 (atan2 (sqrt (fma (cos phi1) t_1 t_2)) t_3)))
(if (<= phi1 8.2e-7)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_4 (* (* (cos phi1) (cos phi2)) t_4))
(pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0))))))
(* R (* 2.0 (atan2 (sqrt (+ t_2 (* (cos phi1) t_1))) t_3)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = pow(sin((0.5 * phi1)), 2.0);
double t_3 = sqrt((pow(cos((0.5 * phi1)), 2.0) - (cos(phi1) * t_0)));
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi1 <= -0.056) {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi1), t_1, t_2)), t_3));
} else if (phi1 <= 8.2e-7) {
tmp = R * (2.0 * atan2(sqrt(((t_4 * ((cos(phi1) * cos(phi2)) * t_4)) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_2 + (cos(phi1) * t_1))), t_3));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = sin(Float64(0.5 * phi1)) ^ 2.0 t_3 = sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - Float64(cos(phi1) * t_0))) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (phi1 <= -0.056) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), t_1, t_2)), t_3))); elseif (phi1 <= 8.2e-7) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_4 * Float64(Float64(cos(phi1) * cos(phi2)) * t_4)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(cos(phi1) * t_1))), t_3))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -0.056], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * t$95$1 + t$95$2), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 8.2e-7], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$4 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := {\sin \left(0.5 \cdot \phi_1\right)}^{2}\\
t_3 := \sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - \cos \phi_1 \cdot t\_0}\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_1 \leq -0.056:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, t\_1, t\_2\right)}}{t\_3}\right)\\
\mathbf{elif}\;\phi_1 \leq 8.2 \cdot 10^{-7}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_4\right) + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + \cos \phi_1 \cdot t\_1}}{t\_3}\right)\\
\end{array}
\end{array}
if phi1 < -0.0560000000000000012Initial program 54.7%
Taylor expanded in phi2 around 0 54.4%
Taylor expanded in phi2 around 0 55.5%
+-commutative7.9%
associate--r+7.9%
unpow27.9%
1-sub-sin7.9%
unpow27.9%
sub-neg7.9%
mul-1-neg7.9%
distribute-lft-in7.9%
metadata-eval7.9%
associate-*r*7.9%
associate-*r*7.9%
metadata-eval7.9%
distribute-lft-in7.9%
+-commutative7.9%
Simplified55.6%
Taylor expanded in phi2 around 0 56.6%
fma-def56.6%
Simplified56.6%
if -0.0560000000000000012 < phi1 < 8.1999999999999998e-7Initial program 78.7%
Taylor expanded in phi1 around 0 78.7%
Simplified78.8%
Taylor expanded in phi1 around 0 77.2%
if 8.1999999999999998e-7 < phi1 Initial program 47.3%
Taylor expanded in phi2 around 0 47.6%
Taylor expanded in phi2 around 0 48.5%
+-commutative7.9%
associate--r+7.9%
unpow27.9%
1-sub-sin7.9%
unpow27.9%
sub-neg7.9%
mul-1-neg7.9%
distribute-lft-in7.9%
metadata-eval7.9%
associate-*r*7.9%
associate-*r*7.9%
metadata-eval7.9%
distribute-lft-in7.9%
+-commutative7.9%
Simplified48.6%
Taylor expanded in phi2 around 0 49.0%
Final simplification65.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))
(if (or (<= phi2 -38000000000.0) (not (<= phi2 7.5e-5)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_1))))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi1)
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- (pow (cos (* 0.5 phi1)) 2.0) (* (cos phi1) 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((-0.5 * (lambda2 - lambda1))), 2.0);
double tmp;
if ((phi2 <= -38000000000.0) || !(phi2 <= 7.5e-5)) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_1)))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi1), pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow(sin((0.5 * phi1)), 2.0))), sqrt((pow(cos((0.5 * phi1)), 2.0) - (cos(phi1) * t_1)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 tmp = 0.0 if ((phi2 <= -38000000000.0) || !(phi2 <= 7.5e-5)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - Float64(cos(phi1) * t_1)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -38000000000.0], N[Not[LessEqual[phi2, 7.5e-5]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -38000000000 \lor \neg \left(\phi_2 \leq 7.5 \cdot 10^{-5}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - \cos \phi_1 \cdot t\_1}}\right)\\
\end{array}
\end{array}
if phi2 < -3.8e10 or 7.49999999999999934e-5 < phi2 Initial program 51.2%
Taylor expanded in phi1 around 0 52.3%
Simplified52.4%
unpow252.4%
sin-mult52.4%
div-inv52.4%
metadata-eval52.4%
div-inv52.4%
metadata-eval52.4%
div-inv52.4%
metadata-eval52.4%
div-inv52.4%
metadata-eval52.4%
Applied egg-rr52.4%
div-sub52.4%
+-inverses52.4%
cos-052.4%
metadata-eval52.4%
distribute-lft-out52.4%
metadata-eval52.4%
*-rgt-identity52.4%
Simplified52.4%
if -3.8e10 < phi2 < 7.49999999999999934e-5Initial program 77.9%
Taylor expanded in phi2 around 0 78.1%
Taylor expanded in phi2 around 0 78.1%
+-commutative7.6%
associate--r+7.6%
unpow27.6%
1-sub-sin7.6%
unpow27.6%
sub-neg7.6%
mul-1-neg7.6%
distribute-lft-in7.6%
metadata-eval7.6%
associate-*r*7.6%
associate-*r*7.6%
metadata-eval7.6%
distribute-lft-in7.6%
+-commutative7.6%
Simplified78.1%
Taylor expanded in phi2 around 0 75.3%
fma-def75.3%
Simplified75.3%
Final simplification64.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
(if (or (<= t_0 -0.0001) (not (<= t_0 5e-12)))
(*
R
(*
2.0
(atan2
t_1
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))
(*
R
(*
2.0
(atan2 t_1 (sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if ((t_0 <= -0.0001) || !(t_0 <= 5e-12)) {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)))
if ((t_0 <= (-0.0001d0)) .or. (.not. (t_0 <= 5d-12))) then
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.sqrt(((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double tmp;
if ((t_0 <= -0.0001) || !(t_0 <= 5e-12)) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt(((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))) tmp = 0 if (t_0 <= -0.0001) or not (t_0 <= 5e-12): tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) tmp = 0.0 if ((t_0 <= -0.0001) || !(t_0 <= 5e-12)) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))); tmp = 0.0; if ((t_0 <= -0.0001) || ~((t_0 <= 5e-12))) tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); else tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[t$95$0, -0.0001], N[Not[LessEqual[t$95$0, 5e-12]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
\mathbf{if}\;t\_0 \leq -0.0001 \lor \neg \left(t\_0 \leq 5 \cdot 10^{-12}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) < -1.00000000000000005e-4 or 4.9999999999999997e-12 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) Initial program 59.7%
Taylor expanded in phi1 around 0 46.7%
Simplified46.7%
Taylor expanded in phi2 around 0 34.8%
if -1.00000000000000005e-4 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) < 4.9999999999999997e-12Initial program 83.3%
Taylor expanded in lambda1 around 0 83.3%
Taylor expanded in lambda2 around 0 82.6%
Final simplification46.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))
(if (or (<= phi2 -38000000000.0) (not (<= phi2 7.5e-5)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_1))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* 0.5 phi1)) 2.0)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt (- (pow (cos (* 0.5 phi1)) 2.0) (* (cos phi1) 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((-0.5 * (lambda2 - lambda1))), 2.0);
double tmp;
if ((phi2 <= -38000000000.0) || !(phi2 <= 7.5e-5)) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_1)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin((0.5 * phi1)), 2.0) + (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt((pow(cos((0.5 * phi1)), 2.0) - (cos(phi1) * t_1)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0
if ((phi2 <= (-38000000000.0d0)) .or. (.not. (phi2 <= 7.5d-5))) then
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * t_1)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin((0.5d0 * phi1)) ** 2.0d0) + (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))), sqrt(((cos((0.5d0 * phi1)) ** 2.0d0) - (cos(phi1) * t_1)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0);
double tmp;
if ((phi2 <= -38000000000.0) || !(phi2 <= 7.5e-5)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * t_1)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((0.5 * phi1)), 2.0) + (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), Math.sqrt((Math.pow(Math.cos((0.5 * phi1)), 2.0) - (Math.cos(phi1) * t_1)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0) tmp = 0 if (phi2 <= -38000000000.0) or not (phi2 <= 7.5e-5): tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * t_1))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((0.5 * phi1)), 2.0) + (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), math.sqrt((math.pow(math.cos((0.5 * phi1)), 2.0) - (math.cos(phi1) * t_1))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 tmp = 0.0 if ((phi2 <= -38000000000.0) || !(phi2 <= 7.5e-5)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(0.5 * phi1)) ^ 2.0) + Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - Float64(cos(phi1) * t_1)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin((-0.5 * (lambda2 - lambda1))) ^ 2.0; tmp = 0.0; if ((phi2 <= -38000000000.0) || ~((phi2 <= 7.5e-5))) tmp = R * (2.0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * t_1))))); else tmp = R * (2.0 * atan2(sqrt(((sin((0.5 * phi1)) ^ 2.0) + (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))), sqrt(((cos((0.5 * phi1)) ^ 2.0) - (cos(phi1) * t_1))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -38000000000.0], N[Not[LessEqual[phi2, 7.5e-5]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -38000000000 \lor \neg \left(\phi_2 \leq 7.5 \cdot 10^{-5}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(0.5 \cdot \phi_1\right)}^{2} + \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}{\sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - \cos \phi_1 \cdot t\_1}}\right)\\
\end{array}
\end{array}
if phi2 < -3.8e10 or 7.49999999999999934e-5 < phi2 Initial program 51.2%
Taylor expanded in phi1 around 0 52.3%
Simplified52.4%
unpow252.4%
sin-mult52.4%
div-inv52.4%
metadata-eval52.4%
div-inv52.4%
metadata-eval52.4%
div-inv52.4%
metadata-eval52.4%
div-inv52.4%
metadata-eval52.4%
Applied egg-rr52.4%
div-sub52.4%
+-inverses52.4%
cos-052.4%
metadata-eval52.4%
distribute-lft-out52.4%
metadata-eval52.4%
*-rgt-identity52.4%
Simplified52.4%
if -3.8e10 < phi2 < 7.49999999999999934e-5Initial program 77.9%
Taylor expanded in phi2 around 0 78.1%
Taylor expanded in phi2 around 0 78.1%
+-commutative7.6%
associate--r+7.6%
unpow27.6%
1-sub-sin7.6%
unpow27.6%
sub-neg7.6%
mul-1-neg7.6%
distribute-lft-in7.6%
metadata-eval7.6%
associate-*r*7.6%
associate-*r*7.6%
metadata-eval7.6%
distribute-lft-in7.6%
+-commutative7.6%
Simplified78.1%
Taylor expanded in phi2 around 0 75.3%
Final simplification64.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt(((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt(((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 65.5%
Taylor expanded in phi1 around 0 51.5%
Simplified51.6%
Taylor expanded in phi2 around 0 36.8%
Final simplification36.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* 0.5 phi1)))
(t_1 (* phi2 t_0))
(t_2
(sqrt
(-
(pow t_0 2.0)
(* (cos phi1) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))
(if (<= phi2 6.8e-133)
(* R (* 2.0 (atan2 (+ (sin (* 0.5 phi1)) (* -0.5 t_1)) t_2)))
(* R (* 2.0 (atan2 (* 0.5 t_1) t_2))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi1));
double t_1 = phi2 * t_0;
double t_2 = sqrt((pow(t_0, 2.0) - (cos(phi1) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))));
double tmp;
if (phi2 <= 6.8e-133) {
tmp = R * (2.0 * atan2((sin((0.5 * phi1)) + (-0.5 * t_1)), t_2));
} else {
tmp = R * (2.0 * atan2((0.5 * t_1), t_2));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = cos((0.5d0 * phi1))
t_1 = phi2 * t_0
t_2 = sqrt(((t_0 ** 2.0d0) - (cos(phi1) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))
if (phi2 <= 6.8d-133) then
tmp = r * (2.0d0 * atan2((sin((0.5d0 * phi1)) + ((-0.5d0) * t_1)), t_2))
else
tmp = r * (2.0d0 * atan2((0.5d0 * t_1), t_2))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos((0.5 * phi1));
double t_1 = phi2 * t_0;
double t_2 = Math.sqrt((Math.pow(t_0, 2.0) - (Math.cos(phi1) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))));
double tmp;
if (phi2 <= 6.8e-133) {
tmp = R * (2.0 * Math.atan2((Math.sin((0.5 * phi1)) + (-0.5 * t_1)), t_2));
} else {
tmp = R * (2.0 * Math.atan2((0.5 * t_1), t_2));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((0.5 * phi1)) t_1 = phi2 * t_0 t_2 = math.sqrt((math.pow(t_0, 2.0) - (math.cos(phi1) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))) tmp = 0 if phi2 <= 6.8e-133: tmp = R * (2.0 * math.atan2((math.sin((0.5 * phi1)) + (-0.5 * t_1)), t_2)) else: tmp = R * (2.0 * math.atan2((0.5 * t_1), t_2)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(0.5 * phi1)) t_1 = Float64(phi2 * t_0) t_2 = sqrt(Float64((t_0 ^ 2.0) - Float64(cos(phi1) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))) tmp = 0.0 if (phi2 <= 6.8e-133) tmp = Float64(R * Float64(2.0 * atan(Float64(sin(Float64(0.5 * phi1)) + Float64(-0.5 * t_1)), t_2))); else tmp = Float64(R * Float64(2.0 * atan(Float64(0.5 * t_1), t_2))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((0.5 * phi1)); t_1 = phi2 * t_0; t_2 = sqrt(((t_0 ^ 2.0) - (cos(phi1) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))); tmp = 0.0; if (phi2 <= 6.8e-133) tmp = R * (2.0 * atan2((sin((0.5 * phi1)) + (-0.5 * t_1)), t_2)); else tmp = R * (2.0 * atan2((0.5 * t_1), t_2)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(phi2 * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(N[Power[t$95$0, 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, 6.8e-133], N[(R * N[(2.0 * N[ArcTan[N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(-0.5 * t$95$1), $MachinePrecision]), $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(0.5 * t$95$1), $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_1\right)\\
t_1 := \phi_2 \cdot t\_0\\
t_2 := \sqrt{{t\_0}^{2} - \cos \phi_1 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}\\
\mathbf{if}\;\phi_2 \leq 6.8 \cdot 10^{-133}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \phi_1\right) + -0.5 \cdot t\_1}{t\_2}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{0.5 \cdot t\_1}{t\_2}\right)\\
\end{array}
\end{array}
if phi2 < 6.80000000000000012e-133Initial program 68.5%
Taylor expanded in phi2 around 0 56.6%
Taylor expanded in phi2 around 0 57.0%
+-commutative10.9%
associate--r+10.9%
unpow210.9%
1-sub-sin10.9%
unpow210.9%
sub-neg10.9%
mul-1-neg10.9%
distribute-lft-in10.9%
metadata-eval10.9%
associate-*r*10.9%
associate-*r*10.9%
metadata-eval10.9%
distribute-lft-in10.9%
+-commutative10.9%
Simplified57.0%
Taylor expanded in phi2 around -inf 16.0%
if 6.80000000000000012e-133 < phi2 Initial program 60.3%
Taylor expanded in phi2 around 0 39.0%
Taylor expanded in phi2 around 0 39.7%
+-commutative6.8%
associate--r+6.8%
unpow26.8%
1-sub-sin6.8%
unpow26.8%
sub-neg6.8%
mul-1-neg6.8%
distribute-lft-in6.8%
metadata-eval6.8%
associate-*r*6.8%
associate-*r*6.8%
metadata-eval6.8%
distribute-lft-in6.8%
+-commutative6.8%
Simplified39.7%
Taylor expanded in phi2 around inf 15.2%
Final simplification15.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* 0.5 phi1)))
(t_1 (* phi2 t_0))
(t_2
(sqrt
(-
(pow t_0 2.0)
(* (cos phi1) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))
(t_3 (sin (* 0.5 phi1))))
(if (<= phi2 -1.85e-87)
(* R (* 2.0 (atan2 (+ t_3 (* -0.5 t_1)) t_2)))
(* R (* 2.0 (atan2 (- (* 0.5 t_1) t_3) t_2))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi1));
double t_1 = phi2 * t_0;
double t_2 = sqrt((pow(t_0, 2.0) - (cos(phi1) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))));
double t_3 = sin((0.5 * phi1));
double tmp;
if (phi2 <= -1.85e-87) {
tmp = R * (2.0 * atan2((t_3 + (-0.5 * t_1)), t_2));
} else {
tmp = R * (2.0 * atan2(((0.5 * t_1) - t_3), t_2));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: tmp
t_0 = cos((0.5d0 * phi1))
t_1 = phi2 * t_0
t_2 = sqrt(((t_0 ** 2.0d0) - (cos(phi1) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))
t_3 = sin((0.5d0 * phi1))
if (phi2 <= (-1.85d-87)) then
tmp = r * (2.0d0 * atan2((t_3 + ((-0.5d0) * t_1)), t_2))
else
tmp = r * (2.0d0 * atan2(((0.5d0 * t_1) - t_3), t_2))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos((0.5 * phi1));
double t_1 = phi2 * t_0;
double t_2 = Math.sqrt((Math.pow(t_0, 2.0) - (Math.cos(phi1) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))));
double t_3 = Math.sin((0.5 * phi1));
double tmp;
if (phi2 <= -1.85e-87) {
tmp = R * (2.0 * Math.atan2((t_3 + (-0.5 * t_1)), t_2));
} else {
tmp = R * (2.0 * Math.atan2(((0.5 * t_1) - t_3), t_2));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((0.5 * phi1)) t_1 = phi2 * t_0 t_2 = math.sqrt((math.pow(t_0, 2.0) - (math.cos(phi1) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))) t_3 = math.sin((0.5 * phi1)) tmp = 0 if phi2 <= -1.85e-87: tmp = R * (2.0 * math.atan2((t_3 + (-0.5 * t_1)), t_2)) else: tmp = R * (2.0 * math.atan2(((0.5 * t_1) - t_3), t_2)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(0.5 * phi1)) t_1 = Float64(phi2 * t_0) t_2 = sqrt(Float64((t_0 ^ 2.0) - Float64(cos(phi1) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))) t_3 = sin(Float64(0.5 * phi1)) tmp = 0.0 if (phi2 <= -1.85e-87) tmp = Float64(R * Float64(2.0 * atan(Float64(t_3 + Float64(-0.5 * t_1)), t_2))); else tmp = Float64(R * Float64(2.0 * atan(Float64(Float64(0.5 * t_1) - t_3), t_2))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((0.5 * phi1)); t_1 = phi2 * t_0; t_2 = sqrt(((t_0 ^ 2.0) - (cos(phi1) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))); t_3 = sin((0.5 * phi1)); tmp = 0.0; if (phi2 <= -1.85e-87) tmp = R * (2.0 * atan2((t_3 + (-0.5 * t_1)), t_2)); else tmp = R * (2.0 * atan2(((0.5 * t_1) - t_3), t_2)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(phi2 * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(N[Power[t$95$0, 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -1.85e-87], N[(R * N[(2.0 * N[ArcTan[N[(t$95$3 + N[(-0.5 * t$95$1), $MachinePrecision]), $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(N[(0.5 * t$95$1), $MachinePrecision] - t$95$3), $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_1\right)\\
t_1 := \phi_2 \cdot t\_0\\
t_2 := \sqrt{{t\_0}^{2} - \cos \phi_1 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}\\
t_3 := \sin \left(0.5 \cdot \phi_1\right)\\
\mathbf{if}\;\phi_2 \leq -1.85 \cdot 10^{-87}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3 + -0.5 \cdot t\_1}{t\_2}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{0.5 \cdot t\_1 - t\_3}{t\_2}\right)\\
\end{array}
\end{array}
if phi2 < -1.8500000000000001e-87Initial program 54.6%
Taylor expanded in phi2 around 0 29.6%
Taylor expanded in phi2 around 0 30.3%
+-commutative14.7%
associate--r+14.7%
unpow214.7%
1-sub-sin14.7%
unpow214.7%
sub-neg14.7%
mul-1-neg14.7%
distribute-lft-in14.7%
metadata-eval14.7%
associate-*r*14.7%
associate-*r*14.7%
metadata-eval14.7%
distribute-lft-in14.7%
+-commutative14.7%
Simplified30.3%
Taylor expanded in phi2 around -inf 17.5%
if -1.8500000000000001e-87 < phi2 Initial program 70.2%
Taylor expanded in phi2 around 0 59.1%
Taylor expanded in phi2 around 0 59.4%
+-commutative7.1%
associate--r+7.1%
unpow27.1%
1-sub-sin7.1%
unpow27.1%
sub-neg7.1%
mul-1-neg7.1%
distribute-lft-in7.1%
metadata-eval7.1%
associate-*r*7.1%
associate-*r*7.1%
metadata-eval7.1%
distribute-lft-in7.1%
+-commutative7.1%
Simplified59.5%
Taylor expanded in phi2 around inf 18.4%
+-commutative18.4%
mul-1-neg18.4%
unsub-neg18.4%
Simplified18.4%
Final simplification18.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* 0.5 phi1)))
(t_1 (* phi2 t_0))
(t_2
(sqrt
(-
(pow t_0 2.0)
(* (cos phi1) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))
(if (<= phi2 -2e-310)
(* R (* 2.0 (atan2 (* -0.5 t_1) t_2)))
(* R (* 2.0 (atan2 (* 0.5 t_1) t_2))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi1));
double t_1 = phi2 * t_0;
double t_2 = sqrt((pow(t_0, 2.0) - (cos(phi1) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))));
double tmp;
if (phi2 <= -2e-310) {
tmp = R * (2.0 * atan2((-0.5 * t_1), t_2));
} else {
tmp = R * (2.0 * atan2((0.5 * t_1), t_2));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = cos((0.5d0 * phi1))
t_1 = phi2 * t_0
t_2 = sqrt(((t_0 ** 2.0d0) - (cos(phi1) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))
if (phi2 <= (-2d-310)) then
tmp = r * (2.0d0 * atan2(((-0.5d0) * t_1), t_2))
else
tmp = r * (2.0d0 * atan2((0.5d0 * t_1), t_2))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos((0.5 * phi1));
double t_1 = phi2 * t_0;
double t_2 = Math.sqrt((Math.pow(t_0, 2.0) - (Math.cos(phi1) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))));
double tmp;
if (phi2 <= -2e-310) {
tmp = R * (2.0 * Math.atan2((-0.5 * t_1), t_2));
} else {
tmp = R * (2.0 * Math.atan2((0.5 * t_1), t_2));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((0.5 * phi1)) t_1 = phi2 * t_0 t_2 = math.sqrt((math.pow(t_0, 2.0) - (math.cos(phi1) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))) tmp = 0 if phi2 <= -2e-310: tmp = R * (2.0 * math.atan2((-0.5 * t_1), t_2)) else: tmp = R * (2.0 * math.atan2((0.5 * t_1), t_2)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(0.5 * phi1)) t_1 = Float64(phi2 * t_0) t_2 = sqrt(Float64((t_0 ^ 2.0) - Float64(cos(phi1) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))) tmp = 0.0 if (phi2 <= -2e-310) tmp = Float64(R * Float64(2.0 * atan(Float64(-0.5 * t_1), t_2))); else tmp = Float64(R * Float64(2.0 * atan(Float64(0.5 * t_1), t_2))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((0.5 * phi1)); t_1 = phi2 * t_0; t_2 = sqrt(((t_0 ^ 2.0) - (cos(phi1) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))); tmp = 0.0; if (phi2 <= -2e-310) tmp = R * (2.0 * atan2((-0.5 * t_1), t_2)); else tmp = R * (2.0 * atan2((0.5 * t_1), t_2)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(phi2 * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(N[Power[t$95$0, 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -2e-310], N[(R * N[(2.0 * N[ArcTan[N[(-0.5 * t$95$1), $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(0.5 * t$95$1), $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_1\right)\\
t_1 := \phi_2 \cdot t\_0\\
t_2 := \sqrt{{t\_0}^{2} - \cos \phi_1 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}\\
\mathbf{if}\;\phi_2 \leq -2 \cdot 10^{-310}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{-0.5 \cdot t\_1}{t\_2}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{0.5 \cdot t\_1}{t\_2}\right)\\
\end{array}
\end{array}
if phi2 < -1.999999999999994e-310Initial program 62.7%
Taylor expanded in phi2 around 0 46.0%
Taylor expanded in phi2 around -inf 11.8%
Taylor expanded in phi2 around 0 12.2%
+-commutative12.2%
associate--r+12.2%
unpow212.2%
1-sub-sin12.2%
unpow212.2%
sub-neg12.2%
mul-1-neg12.2%
distribute-lft-in12.2%
metadata-eval12.2%
associate-*r*12.2%
associate-*r*12.2%
metadata-eval12.2%
distribute-lft-in12.2%
+-commutative12.2%
Simplified12.2%
if -1.999999999999994e-310 < phi2 Initial program 67.8%
Taylor expanded in phi2 around 0 53.7%
Taylor expanded in phi2 around 0 54.1%
+-commutative7.2%
associate--r+7.2%
unpow27.2%
1-sub-sin7.2%
unpow27.2%
sub-neg7.2%
mul-1-neg7.2%
distribute-lft-in7.2%
metadata-eval7.2%
associate-*r*7.2%
associate-*r*7.2%
metadata-eval7.2%
distribute-lft-in7.2%
+-commutative7.2%
Simplified54.2%
Taylor expanded in phi2 around inf 13.0%
Final simplification12.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* 0.5 phi1))))
(*
R
(*
2.0
(atan2
(* -0.5 (* phi2 t_0))
(sqrt
(-
(pow t_0 2.0)
(* (cos phi1) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi1));
return R * (2.0 * atan2((-0.5 * (phi2 * t_0)), sqrt((pow(t_0, 2.0) - (cos(phi1) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = cos((0.5d0 * phi1))
code = r * (2.0d0 * atan2(((-0.5d0) * (phi2 * t_0)), sqrt(((t_0 ** 2.0d0) - (cos(phi1) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos((0.5 * phi1));
return R * (2.0 * Math.atan2((-0.5 * (phi2 * t_0)), Math.sqrt((Math.pow(t_0, 2.0) - (Math.cos(phi1) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((0.5 * phi1)) return R * (2.0 * math.atan2((-0.5 * (phi2 * t_0)), math.sqrt((math.pow(t_0, 2.0) - (math.cos(phi1) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(0.5 * phi1)) return Float64(R * Float64(2.0 * atan(Float64(-0.5 * Float64(phi2 * t_0)), sqrt(Float64((t_0 ^ 2.0) - Float64(cos(phi1) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((0.5 * phi1)); tmp = R * (2.0 * atan2((-0.5 * (phi2 * t_0)), sqrt(((t_0 ^ 2.0) - (cos(phi1) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[(-0.5 * N[(phi2 * t$95$0), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(N[Power[t$95$0, 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_1\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{-0.5 \cdot \left(\phi_2 \cdot t\_0\right)}{\sqrt{{t\_0}^{2} - \cos \phi_1 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 65.5%
Taylor expanded in phi2 around 0 50.2%
Taylor expanded in phi2 around -inf 9.0%
Taylor expanded in phi2 around 0 9.4%
+-commutative9.4%
associate--r+9.4%
unpow29.4%
1-sub-sin9.4%
unpow29.4%
sub-neg9.4%
mul-1-neg9.4%
distribute-lft-in9.4%
metadata-eval9.4%
associate-*r*9.4%
associate-*r*9.4%
metadata-eval9.4%
distribute-lft-in9.4%
+-commutative9.4%
Simplified9.4%
Final simplification9.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(* -0.5 (* phi2 (cos (* 0.5 phi1))))
(sqrt
(- 1.0 (* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2((-0.5 * (phi2 * cos((0.5 * phi1)))), sqrt((1.0 - (cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(((-0.5d0) * (phi2 * cos((0.5d0 * phi1)))), sqrt((1.0d0 - (cos(phi2) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2((-0.5 * (phi2 * Math.cos((0.5 * phi1)))), Math.sqrt((1.0 - (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2((-0.5 * (phi2 * math.cos((0.5 * phi1)))), math.sqrt((1.0 - (math.cos(phi2) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(Float64(-0.5 * Float64(phi2 * cos(Float64(0.5 * phi1)))), sqrt(Float64(1.0 - Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2((-0.5 * (phi2 * cos((0.5 * phi1)))), sqrt((1.0 - (cos(phi2) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[(-0.5 * N[(phi2 * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{-0.5 \cdot \left(\phi_2 \cdot \cos \left(0.5 \cdot \phi_1\right)\right)}{\sqrt{1 - \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
Initial program 65.5%
Taylor expanded in phi2 around 0 50.2%
Taylor expanded in phi2 around -inf 9.0%
Taylor expanded in phi1 around 0 9.4%
Simplified9.4%
Taylor expanded in phi2 around 0 9.4%
Final simplification9.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(* -0.5 (* phi2 (cos (* 0.5 phi1))))
(sqrt (- 1.0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2((-0.5 * (phi2 * cos((0.5 * phi1)))), sqrt((1.0 - pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(((-0.5d0) * (phi2 * cos((0.5d0 * phi1)))), sqrt((1.0d0 - (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2((-0.5 * (phi2 * Math.cos((0.5 * phi1)))), Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2((-0.5 * (phi2 * math.cos((0.5 * phi1)))), math.sqrt((1.0 - math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(Float64(-0.5 * Float64(phi2 * cos(Float64(0.5 * phi1)))), sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2((-0.5 * (phi2 * cos((0.5 * phi1)))), sqrt((1.0 - (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[(-0.5 * N[(phi2 * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{-0.5 \cdot \left(\phi_2 \cdot \cos \left(0.5 \cdot \phi_1\right)\right)}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
Initial program 65.5%
Taylor expanded in phi2 around 0 50.2%
Taylor expanded in phi2 around -inf 9.0%
Taylor expanded in phi1 around 0 9.4%
Simplified9.4%
Taylor expanded in phi2 around 0 9.4%
Final simplification9.4%
herbie shell --seed 2024031
(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))))))))))