
(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
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
t_0))
(sqrt
(-
1.0
(+
t_0
(*
(cos phi1)
(*
(cos phi2)
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
return R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = ((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))) + t_0)), sqrt((1.0d0 - (t_0 + (cos(phi1) * (cos(phi2) * (((sin((lambda1 / 2.0d0)) * cos((lambda2 / 2.0d0))) - (cos((lambda1 / 2.0d0)) * sin((lambda2 / 2.0d0)))) ** 2.0d0))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), Math.sqrt((1.0 - (t_0 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(((Math.sin((lambda1 / 2.0)) * Math.cos((lambda2 / 2.0))) - (Math.cos((lambda1 / 2.0)) * Math.sin((lambda2 / 2.0)))), 2.0))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), math.sqrt((1.0 - (t_0 + (math.cos(phi1) * (math.cos(phi2) * math.pow(((math.sin((lambda1 / 2.0)) * math.cos((lambda2 / 2.0))) - (math.cos((lambda1 / 2.0)) * math.sin((lambda2 / 2.0)))), 2.0))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) + t_0)), sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * Float64(cos(phi2) * (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))) + t_0)), sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * (((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))) ^ 2.0)))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + t\_0}}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right)}^{2}\right)\right)}}\right)
\end{array}
\end{array}
Initial program 58.3%
div-sub58.3%
sin-diff59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
Applied egg-rr59.5%
div-sub58.3%
sin-diff59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
Applied egg-rr78.7%
Taylor expanded in phi1 around 0 78.7%
*-commutative78.7%
metadata-eval78.7%
div-inv78.7%
div-sub78.7%
sin-diff79.2%
Applied egg-rr79.2%
Final simplification79.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (* (cos phi2) t_1))
(t_3 (sqrt (+ (* (cos phi1) t_2) t_0))))
(if (or (<= phi1 -0.062) (not (<= phi1 67000000000.0)))
(* R (* 2.0 (atan2 t_3 (sqrt (- 1.0 (+ t_0 (* (cos phi1) t_1)))))))
(* R (* 2.0 (atan2 t_3 (sqrt (- 1.0 (+ t_2 t_0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = cos(phi2) * t_1;
double t_3 = sqrt(((cos(phi1) * t_2) + t_0));
double tmp;
if ((phi1 <= -0.062) || !(phi1 <= 67000000000.0)) {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - (t_0 + (cos(phi1) * t_1))))));
} else {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - (t_2 + t_0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: tmp
t_0 = ((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
t_1 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_2 = cos(phi2) * t_1
t_3 = sqrt(((cos(phi1) * t_2) + t_0))
if ((phi1 <= (-0.062d0)) .or. (.not. (phi1 <= 67000000000.0d0))) then
tmp = r * (2.0d0 * atan2(t_3, sqrt((1.0d0 - (t_0 + (cos(phi1) * t_1))))))
else
tmp = r * (2.0d0 * atan2(t_3, sqrt((1.0d0 - (t_2 + t_0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
double t_1 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = Math.cos(phi2) * t_1;
double t_3 = Math.sqrt(((Math.cos(phi1) * t_2) + t_0));
double tmp;
if ((phi1 <= -0.062) || !(phi1 <= 67000000000.0)) {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt((1.0 - (t_0 + (Math.cos(phi1) * t_1))))));
} else {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt((1.0 - (t_2 + t_0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) t_1 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_2 = math.cos(phi2) * t_1 t_3 = math.sqrt(((math.cos(phi1) * t_2) + t_0)) tmp = 0 if (phi1 <= -0.062) or not (phi1 <= 67000000000.0): tmp = R * (2.0 * math.atan2(t_3, math.sqrt((1.0 - (t_0 + (math.cos(phi1) * t_1)))))) else: tmp = R * (2.0 * math.atan2(t_3, math.sqrt((1.0 - (t_2 + t_0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(cos(phi2) * t_1) t_3 = sqrt(Float64(Float64(cos(phi1) * t_2) + t_0)) tmp = 0.0 if ((phi1 <= -0.062) || !(phi1 <= 67000000000.0)) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * t_1))))))); else tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 - Float64(t_2 + t_0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; t_1 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_2 = cos(phi2) * t_1; t_3 = sqrt(((cos(phi1) * t_2) + t_0)); tmp = 0.0; if ((phi1 <= -0.062) || ~((phi1 <= 67000000000.0))) tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - (t_0 + (cos(phi1) * t_1)))))); else tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - (t_2 + t_0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, 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[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -0.062], N[Not[LessEqual[phi1, 67000000000.0]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(t$95$2 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \cos \phi_2 \cdot t\_1\\
t_3 := \sqrt{\cos \phi_1 \cdot t\_2 + t\_0}\\
\mathbf{if}\;\phi_1 \leq -0.062 \lor \neg \left(\phi_1 \leq 67000000000\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \left(t\_2 + t\_0\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -0.062 or 6.7e10 < phi1 Initial program 41.3%
div-sub41.3%
sin-diff43.5%
div-inv43.5%
metadata-eval43.5%
div-inv43.5%
metadata-eval43.5%
div-inv43.5%
metadata-eval43.5%
div-inv43.5%
metadata-eval43.5%
Applied egg-rr43.5%
div-sub41.3%
sin-diff43.5%
div-inv43.5%
metadata-eval43.5%
div-inv43.5%
metadata-eval43.5%
div-inv43.5%
metadata-eval43.5%
div-inv43.5%
metadata-eval43.5%
Applied egg-rr78.3%
Taylor expanded in phi1 around 0 78.3%
Taylor expanded in phi2 around 0 55.8%
*-commutative55.8%
Simplified55.8%
if -0.062 < phi1 < 6.7e10Initial program 77.9%
div-sub77.9%
sin-diff78.0%
div-inv78.0%
metadata-eval78.0%
div-inv78.0%
metadata-eval78.0%
div-inv78.0%
metadata-eval78.0%
div-inv78.0%
metadata-eval78.0%
Applied egg-rr78.0%
div-sub77.9%
sin-diff78.0%
div-inv78.0%
metadata-eval78.0%
div-inv78.0%
metadata-eval78.0%
div-inv78.0%
metadata-eval78.0%
div-inv78.0%
metadata-eval78.0%
Applied egg-rr79.1%
Taylor expanded in phi1 around 0 79.1%
Taylor expanded in phi1 around 0 78.6%
Final simplification66.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2
(pow (- (* t_0 (cos (* phi2 0.5))) (* t_1 (sin (* phi2 0.5)))) 2.0))
(t_3 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_4 (* (cos phi2) t_3))
(t_5 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -0.00018) (not (<= phi2 0.00072)))
(*
R
(*
2.0
(atan2 (sqrt (+ (* (cos phi1) t_4) t_2)) (sqrt (- 1.0 (+ t_4 t_2))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (+ t_0 (* -0.5 (* phi2 t_1))) 2.0)
(* t_5 (* (* (cos phi1) (cos phi2)) t_5))))
(sqrt
(-
(+ 1.0 (* phi2 (* t_0 t_1)))
(+ (* (cos phi1) t_3) (pow t_0 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = pow(((t_0 * cos((phi2 * 0.5))) - (t_1 * sin((phi2 * 0.5)))), 2.0);
double t_3 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_4 = cos(phi2) * t_3;
double t_5 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -0.00018) || !(phi2 <= 0.00072)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_4) + t_2)), sqrt((1.0 - (t_4 + t_2)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow((t_0 + (-0.5 * (phi2 * t_1))), 2.0) + (t_5 * ((cos(phi1) * cos(phi2)) * t_5)))), sqrt(((1.0 + (phi2 * (t_0 * t_1))) - ((cos(phi1) * t_3) + pow(t_0, 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: t_5
real(8) :: tmp
t_0 = sin((phi1 * 0.5d0))
t_1 = cos((phi1 * 0.5d0))
t_2 = ((t_0 * cos((phi2 * 0.5d0))) - (t_1 * sin((phi2 * 0.5d0)))) ** 2.0d0
t_3 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_4 = cos(phi2) * t_3
t_5 = sin(((lambda1 - lambda2) / 2.0d0))
if ((phi2 <= (-0.00018d0)) .or. (.not. (phi2 <= 0.00072d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * t_4) + t_2)), sqrt((1.0d0 - (t_4 + t_2)))))
else
tmp = r * (2.0d0 * atan2(sqrt((((t_0 + ((-0.5d0) * (phi2 * t_1))) ** 2.0d0) + (t_5 * ((cos(phi1) * cos(phi2)) * t_5)))), sqrt(((1.0d0 + (phi2 * (t_0 * t_1))) - ((cos(phi1) * t_3) + (t_0 ** 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((phi1 * 0.5));
double t_1 = Math.cos((phi1 * 0.5));
double t_2 = Math.pow(((t_0 * Math.cos((phi2 * 0.5))) - (t_1 * Math.sin((phi2 * 0.5)))), 2.0);
double t_3 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_4 = Math.cos(phi2) * t_3;
double t_5 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -0.00018) || !(phi2 <= 0.00072)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * t_4) + t_2)), Math.sqrt((1.0 - (t_4 + t_2)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow((t_0 + (-0.5 * (phi2 * t_1))), 2.0) + (t_5 * ((Math.cos(phi1) * Math.cos(phi2)) * t_5)))), Math.sqrt(((1.0 + (phi2 * (t_0 * t_1))) - ((Math.cos(phi1) * t_3) + Math.pow(t_0, 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((phi1 * 0.5)) t_1 = math.cos((phi1 * 0.5)) t_2 = math.pow(((t_0 * math.cos((phi2 * 0.5))) - (t_1 * math.sin((phi2 * 0.5)))), 2.0) t_3 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_4 = math.cos(phi2) * t_3 t_5 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (phi2 <= -0.00018) or not (phi2 <= 0.00072): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * t_4) + t_2)), math.sqrt((1.0 - (t_4 + t_2))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow((t_0 + (-0.5 * (phi2 * t_1))), 2.0) + (t_5 * ((math.cos(phi1) * math.cos(phi2)) * t_5)))), math.sqrt(((1.0 + (phi2 * (t_0 * t_1))) - ((math.cos(phi1) * t_3) + math.pow(t_0, 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = Float64(Float64(t_0 * cos(Float64(phi2 * 0.5))) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_3 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_4 = Float64(cos(phi2) * t_3) t_5 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -0.00018) || !(phi2 <= 0.00072)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * t_4) + t_2)), sqrt(Float64(1.0 - Float64(t_4 + t_2)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(t_0 + Float64(-0.5 * Float64(phi2 * t_1))) ^ 2.0) + Float64(t_5 * Float64(Float64(cos(phi1) * cos(phi2)) * t_5)))), sqrt(Float64(Float64(1.0 + Float64(phi2 * Float64(t_0 * t_1))) - Float64(Float64(cos(phi1) * t_3) + (t_0 ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((phi1 * 0.5)); t_1 = cos((phi1 * 0.5)); t_2 = ((t_0 * cos((phi2 * 0.5))) - (t_1 * sin((phi2 * 0.5)))) ^ 2.0; t_3 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_4 = cos(phi2) * t_3; t_5 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((phi2 <= -0.00018) || ~((phi2 <= 0.00072))) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_4) + t_2)), sqrt((1.0 - (t_4 + t_2))))); else tmp = R * (2.0 * atan2(sqrt((((t_0 + (-0.5 * (phi2 * t_1))) ^ 2.0) + (t_5 * ((cos(phi1) * cos(phi2)) * t_5)))), sqrt(((1.0 + (phi2 * (t_0 * t_1))) - ((cos(phi1) * t_3) + (t_0 ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[phi2], $MachinePrecision] * t$95$3), $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.00018], N[Not[LessEqual[phi2, 0.00072]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$4), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$4 + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$0 + N[(-0.5 * N[(phi2 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$5 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(phi2 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$3), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := {\left(t\_0 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_3 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_4 := \cos \phi_2 \cdot t\_3\\
t_5 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -0.00018 \lor \neg \left(\phi_2 \leq 0.00072\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot t\_4 + t\_2}}{\sqrt{1 - \left(t\_4 + t\_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(t\_0 + -0.5 \cdot \left(\phi_2 \cdot t\_1\right)\right)}^{2} + t\_5 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_5\right)}}{\sqrt{\left(1 + \phi_2 \cdot \left(t\_0 \cdot t\_1\right)\right) - \left(\cos \phi_1 \cdot t\_3 + {t\_0}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -1.80000000000000011e-4 or 7.20000000000000045e-4 < phi2 Initial program 45.1%
div-sub45.1%
sin-diff47.2%
div-inv47.2%
metadata-eval47.2%
div-inv47.2%
metadata-eval47.2%
div-inv47.2%
metadata-eval47.2%
div-inv47.2%
metadata-eval47.2%
Applied egg-rr47.2%
div-sub45.1%
sin-diff47.2%
div-inv47.2%
metadata-eval47.2%
div-inv47.2%
metadata-eval47.2%
div-inv47.2%
metadata-eval47.2%
div-inv47.2%
metadata-eval47.2%
Applied egg-rr79.6%
Taylor expanded in phi1 around 0 79.6%
Taylor expanded in phi1 around 0 57.5%
if -1.80000000000000011e-4 < phi2 < 7.20000000000000045e-4Initial program 76.4%
Taylor expanded in phi2 around 0 76.5%
Taylor expanded in phi2 around 0 77.4%
*-commutative77.4%
*-commutative77.4%
Simplified77.4%
Final simplification65.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
t_0))
(sqrt
(+
1.0
(-
(*
(cos phi1)
(* (cos phi2) (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5)))
t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
return R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))) - t_0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = ((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))) + t_0)), sqrt((1.0d0 + ((cos(phi1) * (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0d0) - 0.5d0))) - t_0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), Math.sqrt((1.0 + ((Math.cos(phi1) * (Math.cos(phi2) * ((Math.cos((lambda2 - lambda1)) / 2.0) - 0.5))) - t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), math.sqrt((1.0 + ((math.cos(phi1) * (math.cos(phi2) * ((math.cos((lambda2 - lambda1)) / 2.0) - 0.5))) - t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) + t_0)), sqrt(Float64(1.0 + Float64(Float64(cos(phi1) * Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))) - t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))) + t_0)), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))) - t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + t\_0}}{\sqrt{1 + \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)\right) - t\_0\right)}}\right)
\end{array}
\end{array}
Initial program 58.3%
div-sub58.3%
sin-diff59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
Applied egg-rr59.5%
div-sub58.3%
sin-diff59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
Applied egg-rr78.7%
Taylor expanded in phi1 around 0 78.7%
*-commutative78.7%
metadata-eval78.7%
div-inv78.7%
pow278.7%
sin-mult78.7%
Applied egg-rr78.7%
div-sub78.7%
+-inverses78.7%
+-inverses78.7%
+-inverses78.7%
cos-078.7%
metadata-eval78.7%
associate-*r*78.7%
metadata-eval78.7%
*-lft-identity78.7%
sub-neg78.7%
remove-double-neg78.7%
mul-1-neg78.7%
distribute-neg-in78.7%
+-commutative78.7%
cos-neg78.7%
mul-1-neg78.7%
unsub-neg78.7%
Simplified78.7%
Final simplification78.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(+
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + t_1)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - ((((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0) + t_1)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((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.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0) + 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) 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.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) + t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64((Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + t_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 - ((((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0) + t_1))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + 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(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 58.3%
div-sub58.3%
sin-diff59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
Applied egg-rr59.5%
Final simplification59.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
t_1))
(sqrt (+ 1.0 (- (- (/ (cos (- phi1 phi2)) 2.0) 0.5) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + t_1)), sqrt((1.0 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt(((((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0) + t_1)), sqrt((1.0d0 + (((cos((phi1 - phi2)) / 2.0d0) - 0.5d0) - t_1)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0) + t_1)), Math.sqrt((1.0 + (((Math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) + t_1)), math.sqrt((1.0 + (((math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + t_1)), 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(((((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0) + t_1)), sqrt((1.0 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $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{{\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + t\_1}}{\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 58.3%
div-sub58.3%
sin-diff59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
Applied egg-rr59.5%
div-sub58.3%
sin-diff59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
Applied egg-rr78.7%
sin-diff59.4%
metadata-eval59.4%
div-inv59.4%
metadata-eval59.4%
div-inv59.4%
div-sub59.4%
div-inv59.4%
metadata-eval59.4%
*-commutative59.4%
*-commutative59.4%
metadata-eval59.4%
div-inv59.4%
unpow259.4%
sin-mult59.5%
Applied egg-rr59.5%
div-sub59.5%
+-inverses59.5%
cos-059.5%
metadata-eval59.5%
distribute-rgt-out59.5%
metadata-eval59.5%
*-rgt-identity59.5%
Simplified59.5%
Final simplification59.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(atan2
(sqrt
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(sqrt
(+
1.0
(-
(* (cos phi1) (* (cos phi2) (- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))
(* R 2.0)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))) + pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0))), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) - pow(sin((0.5 * (phi1 - phi2))), 2.0))))) * (R * 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 = atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))) + (((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0))), sqrt((1.0d0 + ((cos(phi1) * (cos(phi2) * ((0.5d0 * cos((lambda1 - lambda2))) - 0.5d0))) - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0))))) * (r * 2.0d0)
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0))), Math.sqrt((1.0 + ((Math.cos(phi1) * (Math.cos(phi2) * ((0.5 * Math.cos((lambda1 - lambda2))) - 0.5))) - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0))))) * (R * 2.0);
}
def code(R, lambda1, lambda2, phi1, phi2): return math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0))), math.sqrt((1.0 + ((math.cos(phi1) * (math.cos(phi2) * ((0.5 * math.cos((lambda1 - lambda2))) - 0.5))) - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) * (R * 2.0)
function code(R, lambda1, lambda2, phi1, phi2) return Float64(atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) + (Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0))), sqrt(Float64(1.0 + Float64(Float64(cos(phi1) * Float64(cos(phi2) * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))) - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))) * Float64(R * 2.0)) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))) + (((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0))), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))) * (R * 2.0); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}}}{\sqrt{1 + \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)\right) - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)
\end{array}
Initial program 58.3%
Simplified58.3%
Applied egg-rr43.0%
unpow143.0%
Simplified43.0%
*-commutative43.0%
metadata-eval43.0%
div-inv43.0%
div-sub43.0%
sin-diff43.3%
Applied egg-rr43.3%
fma-neg43.3%
distribute-rgt-neg-in43.3%
Simplified43.3%
Taylor expanded in phi1 around 0 59.4%
Final simplification59.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(fabs
(+
-1.0
(fma
t_0
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(fabs((-1.0 + fma(t_0, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(abs(Float64(-1.0 + fma(t_0, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(-1.0 + N[(t$95$0 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left|-1 + \mathsf{fma}\left(t\_0, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 58.3%
Applied egg-rr58.9%
unpow1/258.9%
unpow258.9%
rem-sqrt-square58.9%
fma-define58.9%
*-commutative58.9%
fma-define58.9%
Simplified58.9%
Final simplification58.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (* t_1 (* t_0 t_0)))
(t_3 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (or (<= phi1 -3.1e+22) (not (<= phi1 1.05e-5)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (* t_1 t_0)) t_3))
(sqrt
(-
1.0
(+
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* phi1 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_3 t_2))
(sqrt (- (+ 1.0 (- (/ (cos (- phi2)) 2.0) 0.5)) t_2))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = t_1 * (t_0 * t_0);
double t_3 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi1 <= -3.1e+22) || !(phi1 <= 1.05e-5)) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_0)) + t_3)), sqrt((1.0 - ((cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_3 + t_2)), sqrt(((1.0 + ((cos(-phi2) / 2.0) - 0.5)) - 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 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
t_2 = t_1 * (t_0 * t_0)
t_3 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
if ((phi1 <= (-3.1d+22)) .or. (.not. (phi1 <= 1.05d-5))) then
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * (t_1 * t_0)) + t_3)), sqrt((1.0d0 - ((cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (sin((phi1 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_3 + t_2)), sqrt(((1.0d0 + ((cos(-phi2) / 2.0d0) - 0.5d0)) - 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.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double t_2 = t_1 * (t_0 * t_0);
double t_3 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi1 <= -3.1e+22) || !(phi1 <= 1.05e-5)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (t_1 * t_0)) + t_3)), Math.sqrt((1.0 - ((Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + t_2)), Math.sqrt(((1.0 + ((Math.cos(-phi2) / 2.0) - 0.5)) - t_2))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) t_2 = t_1 * (t_0 * t_0) t_3 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) tmp = 0 if (phi1 <= -3.1e+22) or not (phi1 <= 1.05e-5): tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * (t_1 * t_0)) + t_3)), math.sqrt((1.0 - ((math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + math.pow(math.sin((phi1 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_3 + t_2)), math.sqrt(((1.0 + ((math.cos(-phi2) / 2.0) - 0.5)) - t_2)))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = Float64(t_1 * Float64(t_0 * t_0)) t_3 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if ((phi1 <= -3.1e+22) || !(phi1 <= 1.05e-5)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_1 * t_0)) + t_3)), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + t_2)), sqrt(Float64(Float64(1.0 + Float64(Float64(cos(Float64(-phi2)) / 2.0) - 0.5)) - t_2))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); t_2 = t_1 * (t_0 * t_0); t_3 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = 0.0; if ((phi1 <= -3.1e+22) || ~((phi1 <= 1.05e-5))) tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_0)) + t_3)), sqrt((1.0 - ((cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + (sin((phi1 * 0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((t_3 + t_2)), sqrt(((1.0 + ((cos(-phi2) / 2.0) - 0.5)) - t_2)))); 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -3.1e+22], N[Not[LessEqual[phi1, 1.05e-5]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(N[(N[Cos[(-phi2)], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := t\_1 \cdot \left(t\_0 \cdot t\_0\right)\\
t_3 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -3.1 \cdot 10^{+22} \lor \neg \left(\phi_1 \leq 1.05 \cdot 10^{-5}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_1 \cdot t\_0\right) + t\_3}}{\sqrt{1 - \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + t\_2}}{\sqrt{\left(1 + \left(\frac{\cos \left(-\phi_2\right)}{2} - 0.5\right)\right) - t\_2}}\right)\\
\end{array}
\end{array}
if phi1 < -3.1000000000000002e22 or 1.04999999999999994e-5 < phi1 Initial program 42.6%
Taylor expanded in phi2 around 0 43.7%
if -3.1000000000000002e22 < phi1 < 1.04999999999999994e-5Initial program 75.8%
associate-*l*75.8%
Simplified75.8%
expm1-log1p-u75.8%
expm1-undefine75.8%
log1p-undefine75.8%
add-exp-log75.8%
div-inv75.8%
metadata-eval75.8%
Applied egg-rr75.8%
Taylor expanded in phi1 around 0 75.8%
neg-mul-175.8%
Simplified75.8%
add-exp-log75.8%
expm1-define75.8%
log1p-define75.8%
expm1-log1p-u75.8%
unpow275.8%
sin-mult75.9%
*-commutative75.9%
*-commutative75.9%
*-commutative75.9%
*-commutative75.9%
Applied egg-rr75.9%
div-sub75.9%
+-inverses75.9%
cos-075.9%
metadata-eval75.9%
distribute-rgt-out75.9%
metadata-eval75.9%
*-rgt-identity75.9%
Simplified75.9%
Final simplification58.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -9.5e-6) (not (<= phi1 6.5e-6)))
(*
R
(*
2.0
(atan2
t_1
(sqrt (- 1.0 (+ (* (cos phi1) t_2) (pow (sin (* phi1 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
t_1
(sqrt
(- 1.0 (+ (* (cos phi2) t_2) (pow (sin (* phi2 -0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -9.5e-6) || !(phi1 <= 6.5e-6)) {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - ((cos(phi1) * t_2) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - ((cos(phi2) * t_2) + pow(sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)))
t_2 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
if ((phi1 <= (-9.5d-6)) .or. (.not. (phi1 <= 6.5d-6))) then
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - ((cos(phi1) * t_2) + (sin((phi1 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - ((cos(phi2) * t_2) + (sin((phi2 * (-0.5d0))) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.sqrt(((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_2 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -9.5e-6) || !(phi1 <= 6.5e-6)) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - ((Math.cos(phi1) * t_2) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - ((Math.cos(phi2) * t_2) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt(((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))) t_2 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) tmp = 0 if (phi1 <= -9.5e-6) or not (phi1 <= 6.5e-6): tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - ((math.cos(phi1) * t_2) + math.pow(math.sin((phi1 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - ((math.cos(phi2) * t_2) + math.pow(math.sin((phi2 * -0.5)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -9.5e-6) || !(phi1 <= 6.5e-6)) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_2) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_2) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))); t_2 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; tmp = 0.0; if ((phi1 <= -9.5e-6) || ~((phi1 <= 6.5e-6))) tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - ((cos(phi1) * t_2) + (sin((phi1 * 0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - ((cos(phi2) * t_2) + (sin((phi2 * -0.5)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -9.5e-6], N[Not[LessEqual[phi1, 6.5e-6]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -9.5 \cdot 10^{-6} \lor \neg \left(\phi_1 \leq 6.5 \cdot 10^{-6}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_2 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -9.5000000000000005e-6 or 6.4999999999999996e-6 < phi1 Initial program 41.3%
Taylor expanded in phi2 around 0 42.3%
if -9.5000000000000005e-6 < phi1 < 6.4999999999999996e-6Initial program 79.5%
Taylor expanded in phi1 around 0 79.5%
Final simplification58.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2
(+
(* t_1 (* (* (cos phi1) (cos phi2)) t_1))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(if (or (<= phi2 -2e-5) (not (<= phi2 8.5e-6)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) t_0) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- 1.0 t_2)))))
(*
R
(*
2.0
(atan2
(sqrt t_2)
(sqrt
(- 1.0 (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (t_1 * ((cos(phi1) * cos(phi2)) * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi2 <= -2e-5) || !(phi2 <= 8.5e-6)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - ((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = (t_1 * ((cos(phi1) * cos(phi2)) * t_1)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)
if ((phi2 <= (-2d-5)) .or. (.not. (phi2 <= 8.5d-6))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * t_0) + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt((1.0d0 - t_2))))
else
tmp = r * (2.0d0 * atan2(sqrt(t_2), sqrt((1.0d0 - ((cos(phi1) * t_0) + (sin((phi1 * 0.5d0)) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = (t_1 * ((Math.cos(phi1) * Math.cos(phi2)) * t_1)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi2 <= -2e-5) || !(phi2 <= 8.5e-6)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * t_0) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(t_2), Math.sqrt((1.0 - ((Math.cos(phi1) * t_0) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = (t_1 * ((math.cos(phi1) * math.cos(phi2)) * t_1)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) tmp = 0 if (phi2 <= -2e-5) or not (phi2 <= 8.5e-6): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * t_0) + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((1.0 - t_2)))) else: tmp = R * (2.0 * math.atan2(math.sqrt(t_2), math.sqrt((1.0 - ((math.cos(phi1) * t_0) + math.pow(math.sin((phi1 * 0.5)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) tmp = 0.0 if ((phi2 <= -2e-5) || !(phi2 <= 8.5e-6)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = (t_1 * ((cos(phi1) * cos(phi2)) * t_1)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0); tmp = 0.0; if ((phi2 <= -2e-5) || ~((phi2 <= 8.5e-6))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + (sin((phi2 * -0.5)) ^ 2.0))), sqrt((1.0 - t_2)))); else tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - ((cos(phi1) * t_0) + (sin((phi1 * 0.5)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -2e-5], N[Not[LessEqual[phi2, 8.5e-6]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -2 \cdot 10^{-5} \lor \neg \left(\phi_2 \leq 8.5 \cdot 10^{-6}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -2.00000000000000016e-5 or 8.4999999999999999e-6 < phi2 Initial program 45.1%
expm1-log1p-u45.1%
expm1-undefine45.1%
log1p-undefine45.1%
add-exp-log45.1%
div-inv45.1%
metadata-eval45.1%
Applied egg-rr44.9%
Taylor expanded in phi1 around 0 45.7%
if -2.00000000000000016e-5 < phi2 < 8.4999999999999999e-6Initial program 76.4%
Taylor expanded in phi2 around 0 76.4%
Final simplification58.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (sin (* 0.5 (- lambda1 lambda2))))
(t_3 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -2.9e-15) (not (<= phi2 1.36)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) (pow t_2 2.0)) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
1.0
(+ (* t_1 (* t_3 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))))
(*
(* R 2.0)
(atan2
(hypot t_0 (* t_2 (sqrt t_3)))
(sqrt
(-
1.0
(fma
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
t_3
(pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sin((0.5 * (lambda1 - lambda2)));
double t_3 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -2.9e-15) || !(phi2 <= 1.36)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(t_2, 2.0)) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - ((t_1 * (t_3 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_0, (t_2 * sqrt(t_3))), sqrt((1.0 - fma((0.5 - (0.5 * cos((lambda1 - lambda2)))), t_3, pow(t_0, 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_3 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -2.9e-15) || !(phi2 <= 1.36)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (t_2 ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(t_1 * Float64(t_3 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(t_2 * sqrt(t_3))), sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), t_3, (t_0 ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -2.9e-15], N[Not[LessEqual[phi2, 1.36]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$1 * N[(t$95$3 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(t$95$2 * N[Sqrt[t$95$3], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$3 + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -2.9 \cdot 10^{-15} \lor \neg \left(\phi_2 \leq 1.36\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {t\_2}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - \left(t\_1 \cdot \left(t\_3 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, t\_2 \cdot \sqrt{t\_3}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_3, {t\_0}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -2.90000000000000019e-15 or 1.3600000000000001 < phi2 Initial program 46.1%
expm1-log1p-u46.1%
expm1-undefine46.1%
log1p-undefine46.1%
add-exp-log46.1%
div-inv46.1%
metadata-eval46.1%
Applied egg-rr45.9%
Taylor expanded in phi1 around 0 46.4%
if -2.90000000000000019e-15 < phi2 < 1.3600000000000001Initial program 75.5%
Simplified75.5%
Applied egg-rr62.3%
unpow162.3%
Simplified62.3%
Final simplification53.0%
(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 58.3%
unpow258.3%
sin-mult58.4%
div-inv58.4%
metadata-eval58.4%
div-inv58.4%
metadata-eval58.4%
div-inv58.4%
metadata-eval58.4%
div-inv58.4%
metadata-eval58.4%
Applied egg-rr58.4%
div-sub58.4%
+-inverses58.4%
cos-058.4%
metadata-eval58.4%
distribute-lft-out58.4%
metadata-eval58.4%
*-rgt-identity58.4%
Simplified58.4%
Final simplification58.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (* 0.5 (- lambda1 lambda2))))
(t_3 (sin (* 0.5 (- phi1 phi2)))))
(if (or (<= phi1 -3.1e-7) (not (<= phi1 3.1e-12)))
(*
(* R 2.0)
(atan2
(hypot (sin (* phi1 0.5)) (* t_2 (sqrt (cos phi1))))
(sqrt (- 1.0 (fma t_0 t_1 (pow t_3 2.0))))))
(*
(* R 2.0)
(atan2
(hypot t_3 (* t_2 (sqrt t_1)))
(sqrt (- 1.0 (fma t_0 t_1 (pow (sin (* phi2 -0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = 0.5 - (0.5 * cos((lambda1 - lambda2)));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin((0.5 * (lambda1 - lambda2)));
double t_3 = sin((0.5 * (phi1 - phi2)));
double tmp;
if ((phi1 <= -3.1e-7) || !(phi1 <= 3.1e-12)) {
tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), (t_2 * sqrt(cos(phi1)))), sqrt((1.0 - fma(t_0, t_1, pow(t_3, 2.0)))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_3, (t_2 * sqrt(t_1))), sqrt((1.0 - fma(t_0, t_1, pow(sin((phi2 * -0.5)), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_3 = sin(Float64(0.5 * Float64(phi1 - phi2))) tmp = 0.0 if ((phi1 <= -3.1e-7) || !(phi1 <= 3.1e-12)) tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), Float64(t_2 * sqrt(cos(phi1)))), sqrt(Float64(1.0 - fma(t_0, t_1, (t_3 ^ 2.0)))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_3, Float64(t_2 * sqrt(t_1))), sqrt(Float64(1.0 - fma(t_0, t_1, (sin(Float64(phi2 * -0.5)) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -3.1e-7], N[Not[LessEqual[phi1, 3.1e-12]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$2 * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * t$95$1 + N[Power[t$95$3, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$3 ^ 2 + N[(t$95$2 * N[Sqrt[t$95$1], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * t$95$1 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_3 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
\mathbf{if}\;\phi_1 \leq -3.1 \cdot 10^{-7} \lor \neg \left(\phi_1 \leq 3.1 \cdot 10^{-12}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), t\_2 \cdot \sqrt{\cos \phi_1}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_0, t\_1, {t\_3}^{2}\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_3, t\_2 \cdot \sqrt{t\_1}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_0, t\_1, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi1 < -3.1e-7 or 3.1000000000000001e-12 < phi1 Initial program 41.6%
Simplified41.6%
Applied egg-rr25.4%
unpow125.4%
Simplified25.4%
Taylor expanded in phi2 around 0 25.1%
Taylor expanded in phi2 around 0 26.4%
if -3.1e-7 < phi1 < 3.1000000000000001e-12Initial program 79.5%
Simplified79.5%
Applied egg-rr65.2%
unpow165.2%
Simplified65.2%
Taylor expanded in phi1 around 0 65.2%
*-commutative65.2%
Simplified65.2%
Final simplification43.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (pow t_0 2.0))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (hypot t_0 (* (sin (* 0.5 (- lambda1 lambda2))) (sqrt t_2)))))
(if (or (<= lambda2 -0.00018) (not (<= lambda2 5e-6)))
(*
(* R 2.0)
(atan2 t_3 (sqrt (- 1.0 (fma (- 0.5 (* 0.5 (cos lambda2))) t_2 t_1)))))
(*
(* R 2.0)
(atan2
t_3
(sqrt (- 1.0 (fma (- 0.5 (* 0.5 (cos lambda1))) t_2 t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = pow(t_0, 2.0);
double t_2 = cos(phi1) * cos(phi2);
double t_3 = hypot(t_0, (sin((0.5 * (lambda1 - lambda2))) * sqrt(t_2)));
double tmp;
if ((lambda2 <= -0.00018) || !(lambda2 <= 5e-6)) {
tmp = (R * 2.0) * atan2(t_3, sqrt((1.0 - fma((0.5 - (0.5 * cos(lambda2))), t_2, t_1))));
} else {
tmp = (R * 2.0) * atan2(t_3, sqrt((1.0 - fma((0.5 - (0.5 * cos(lambda1))), t_2, t_1))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = t_0 ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = hypot(t_0, Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(t_2))) tmp = 0.0 if ((lambda2 <= -0.00018) || !(lambda2 <= 5e-6)) tmp = Float64(Float64(R * 2.0) * atan(t_3, sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(lambda2))), t_2, t_1))))); else tmp = Float64(Float64(R * 2.0) * atan(t_3, sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(lambda1))), t_2, t_1))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[t$95$0, 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[t$95$0 ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[t$95$2], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]}, If[Or[LessEqual[lambda2, -0.00018], N[Not[LessEqual[lambda2, 5e-6]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$2 + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[lambda1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$2 + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := {t\_0}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \mathsf{hypot}\left(t\_0, \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{t\_2}\right)\\
\mathbf{if}\;\lambda_2 \leq -0.00018 \lor \neg \left(\lambda_2 \leq 5 \cdot 10^{-6}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \lambda_2, t\_2, t\_1\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \lambda_1, t\_2, t\_1\right)}}\\
\end{array}
\end{array}
if lambda2 < -1.80000000000000011e-4 or 5.00000000000000041e-6 < lambda2 Initial program 45.7%
Simplified45.7%
Applied egg-rr35.1%
unpow135.1%
Simplified35.1%
Taylor expanded in lambda1 around 0 35.6%
cos-neg35.6%
Simplified35.6%
if -1.80000000000000011e-4 < lambda2 < 5.00000000000000041e-6Initial program 71.3%
Simplified71.3%
Applied egg-rr51.1%
unpow151.1%
Simplified51.1%
Taylor expanded in lambda2 around 0 51.1%
Final simplification43.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* 0.5 (- phi1 phi2))))
(t_2 (sin (* 0.5 (- lambda1 lambda2))))
(t_3 (pow t_1 2.0)))
(if (or (<= lambda2 -2.85e-7) (not (<= lambda2 0.00012)))
(*
(* R 2.0)
(atan2
(hypot (sin (* phi1 0.5)) (* t_2 (sqrt (cos phi1))))
(sqrt (- 1.0 (fma (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))) t_0 t_3)))))
(*
(* R 2.0)
(atan2
(hypot t_1 (* t_2 (sqrt t_0)))
(sqrt (- 1.0 (fma (- 0.5 (* 0.5 (cos lambda1))) t_0 t_3))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((0.5 * (phi1 - phi2)));
double t_2 = sin((0.5 * (lambda1 - lambda2)));
double t_3 = pow(t_1, 2.0);
double tmp;
if ((lambda2 <= -2.85e-7) || !(lambda2 <= 0.00012)) {
tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), (t_2 * sqrt(cos(phi1)))), sqrt((1.0 - fma((0.5 - (0.5 * cos((lambda1 - lambda2)))), t_0, t_3))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_1, (t_2 * sqrt(t_0))), sqrt((1.0 - fma((0.5 - (0.5 * cos(lambda1))), t_0, t_3))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_3 = t_1 ^ 2.0 tmp = 0.0 if ((lambda2 <= -2.85e-7) || !(lambda2 <= 0.00012)) tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), Float64(t_2 * sqrt(cos(phi1)))), sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), t_0, t_3))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_1, Float64(t_2 * sqrt(t_0))), sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(lambda1))), t_0, t_3))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[t$95$1, 2.0], $MachinePrecision]}, If[Or[LessEqual[lambda2, -2.85e-7], N[Not[LessEqual[lambda2, 0.00012]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$2 * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0 + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[(t$95$2 * N[Sqrt[t$95$0], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[lambda1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0 + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_2 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_3 := {t\_1}^{2}\\
\mathbf{if}\;\lambda_2 \leq -2.85 \cdot 10^{-7} \lor \neg \left(\lambda_2 \leq 0.00012\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), t\_2 \cdot \sqrt{\cos \phi_1}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_0, t\_3\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, t\_2 \cdot \sqrt{t\_0}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \lambda_1, t\_0, t\_3\right)}}\\
\end{array}
\end{array}
if lambda2 < -2.8500000000000002e-7 or 1.20000000000000003e-4 < lambda2 Initial program 45.4%
Simplified45.4%
Applied egg-rr34.8%
unpow134.8%
Simplified34.8%
Taylor expanded in phi2 around 0 29.0%
Taylor expanded in phi2 around 0 31.3%
if -2.8500000000000002e-7 < lambda2 < 1.20000000000000003e-4Initial program 71.9%
Simplified71.9%
Applied egg-rr51.5%
unpow151.5%
Simplified51.5%
Taylor expanded in lambda2 around 0 51.5%
Final simplification41.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* 0.5 (- phi1 phi2))))
(t_2
(sqrt
(-
1.0
(fma
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
t_0
(pow t_1 2.0))))))
(if (or (<= lambda2 -5e-8) (not (<= lambda2 1.1e-13)))
(*
(* R 2.0)
(atan2
(hypot
(sin (* phi1 0.5))
(* (sin (* 0.5 (- lambda1 lambda2))) (sqrt (cos phi1))))
t_2))
(*
(* R 2.0)
(atan2 (hypot t_1 (* (sqrt t_0) (sin (* 0.5 lambda1)))) t_2)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((0.5 * (phi1 - phi2)));
double t_2 = sqrt((1.0 - fma((0.5 - (0.5 * cos((lambda1 - lambda2)))), t_0, pow(t_1, 2.0))));
double tmp;
if ((lambda2 <= -5e-8) || !(lambda2 <= 1.1e-13)) {
tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), (sin((0.5 * (lambda1 - lambda2))) * sqrt(cos(phi1)))), t_2);
} else {
tmp = (R * 2.0) * atan2(hypot(t_1, (sqrt(t_0) * sin((0.5 * lambda1)))), t_2);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_2 = sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), t_0, (t_1 ^ 2.0)))) tmp = 0.0 if ((lambda2 <= -5e-8) || !(lambda2 <= 1.1e-13)) tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(cos(phi1)))), t_2)); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_1, Float64(sqrt(t_0) * sin(Float64(0.5 * lambda1)))), t_2)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0 + N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda2, -5e-8], N[Not[LessEqual[lambda2, 1.1e-13]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[(N[Sqrt[t$95$0], $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_2 := \sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_0, {t\_1}^{2}\right)}\\
\mathbf{if}\;\lambda_2 \leq -5 \cdot 10^{-8} \lor \neg \left(\lambda_2 \leq 1.1 \cdot 10^{-13}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_1}\right)}{t\_2}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, \sqrt{t\_0} \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}{t\_2}\\
\end{array}
\end{array}
if lambda2 < -4.9999999999999998e-8 or 1.09999999999999998e-13 < lambda2 Initial program 45.8%
Simplified45.8%
Applied egg-rr34.6%
unpow134.6%
Simplified34.6%
Taylor expanded in phi2 around 0 28.7%
Taylor expanded in phi2 around 0 31.1%
if -4.9999999999999998e-8 < lambda2 < 1.09999999999999998e-13Initial program 72.7%
Simplified72.7%
Applied egg-rr52.6%
unpow152.6%
Simplified52.6%
Taylor expanded in lambda2 around 0 50.3%
Final simplification40.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2))) (t_1 (sin (* 0.5 (- phi1 phi2)))))
(*
(* R 2.0)
(atan2
(hypot t_1 (* (sin (* 0.5 (- lambda1 lambda2))) (sqrt t_0)))
(sqrt
(-
1.0
(fma (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))) t_0 (pow t_1 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((0.5 * (phi1 - phi2)));
return (R * 2.0) * atan2(hypot(t_1, (sin((0.5 * (lambda1 - lambda2))) * sqrt(t_0))), sqrt((1.0 - fma((0.5 - (0.5 * cos((lambda1 - lambda2)))), t_0, pow(t_1, 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) return Float64(Float64(R * 2.0) * atan(hypot(t_1, Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(t_0))), sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), t_0, (t_1 ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[t$95$0], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0 + N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{t\_0}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_0, {t\_1}^{2}\right)}}
\end{array}
\end{array}
Initial program 58.3%
Simplified58.3%
Applied egg-rr43.0%
unpow143.0%
Simplified43.0%
Final simplification43.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(hypot
(sin (* phi1 0.5))
(* (sin (* 0.5 (- lambda1 lambda2))) (sqrt (cos phi1))))
(sqrt
(-
1.0
(fma
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(* (cos phi1) (cos phi2))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), (sin((0.5 * (lambda1 - lambda2))) * sqrt(cos(phi1)))), sqrt((1.0 - fma((0.5 - (0.5 * cos((lambda1 - lambda2)))), (cos(phi1) * cos(phi2)), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(cos(phi1)))), sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), Float64(cos(phi1) * cos(phi2)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_1}\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), \cos \phi_1 \cdot \cos \phi_2, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}
\end{array}
Initial program 58.3%
Simplified58.3%
Applied egg-rr43.0%
unpow143.0%
Simplified43.0%
Taylor expanded in phi2 around 0 30.5%
Taylor expanded in phi2 around 0 32.7%
Final simplification32.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(*
(sin (* 0.5 (- lambda1 lambda2)))
(sqrt
(+
1.0
(* (pow phi2 2.0) (- (* (pow phi2 2.0) 0.041666666666666664) 0.5)))))
(sqrt
(-
1.0
(fma
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(* (cos phi1) (cos phi2))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * atan2((sin((0.5 * (lambda1 - lambda2))) * sqrt((1.0 + (pow(phi2, 2.0) * ((pow(phi2, 2.0) * 0.041666666666666664) - 0.5))))), sqrt((1.0 - fma((0.5 - (0.5 * cos((lambda1 - lambda2)))), (cos(phi1) * cos(phi2)), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * 2.0) * atan(Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(Float64(1.0 + Float64((phi2 ^ 2.0) * Float64(Float64((phi2 ^ 2.0) * 0.041666666666666664) - 0.5))))), sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), Float64(cos(phi1) * cos(phi2)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(1.0 + N[(N[Power[phi2, 2.0], $MachinePrecision] * N[(N[(N[Power[phi2, 2.0], $MachinePrecision] * 0.041666666666666664), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{1 + {\phi_2}^{2} \cdot \left({\phi_2}^{2} \cdot 0.041666666666666664 - 0.5\right)}}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), \cos \phi_1 \cdot \cos \phi_2, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}
\end{array}
Initial program 58.3%
Simplified58.3%
Applied egg-rr43.0%
unpow143.0%
Simplified43.0%
Taylor expanded in phi2 around 0 30.5%
Taylor expanded in phi1 around 0 12.8%
Taylor expanded in phi2 around 0 15.1%
Final simplification15.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(sin (* 0.5 (- lambda1 lambda2)))
(sqrt
(-
1.0
(fma
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(* (cos phi1) (cos phi2))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * atan2(sin((0.5 * (lambda1 - lambda2))), sqrt((1.0 - fma((0.5 - (0.5 * cos((lambda1 - lambda2)))), (cos(phi1) * cos(phi2)), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * 2.0) * atan(sin(Float64(0.5 * Float64(lambda1 - lambda2))), sqrt(Float64(1.0 - fma(Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), Float64(cos(phi1) * cos(phi2)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}{\sqrt{1 - \mathsf{fma}\left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), \cos \phi_1 \cdot \cos \phi_2, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}
\end{array}
Initial program 58.3%
Simplified58.3%
Applied egg-rr43.0%
unpow143.0%
Simplified43.0%
Taylor expanded in phi2 around 0 30.5%
Taylor expanded in phi1 around 0 12.8%
Taylor expanded in phi2 around 0 15.0%
Final simplification15.0%
herbie shell --seed 2024143
(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))))))))))