
(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 15 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}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(if (<= phi1 -2.1e-7)
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (* phi1 0.5)) 2.0)))
(sqrt
(-
(pow (cos (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt
(-
(- 1.0 (pow (sin (* phi2 -0.5)) 2.0))
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
double tmp;
if (phi1 <= -2.1e-7) {
tmp = R * (2.0 * atan2(sqrt((t_1 + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt(((1.0 - pow(sin((phi2 * -0.5)), 2.0)) - (cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0))))));
}
return tmp;
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
if (phi1 <= (-2.1d-7)) then
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (cos(phi1) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt(((1.0d0 - (sin((phi2 * (-0.5d0))) ** 2.0d0)) - (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0))))))
end if
code = tmp
end function
assert phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
double tmp;
if (phi1 <= -2.1e-7) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (Math.cos(phi1) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt(((1.0 - Math.pow(Math.sin((phi2 * -0.5)), 2.0)) - (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0))))));
}
return tmp;
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) tmp = 0 if phi1 <= -2.1e-7: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (math.cos(phi1) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt(((1.0 - math.pow(math.sin((phi2 * -0.5)), 2.0)) - (math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))))) return tmp
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) tmp = 0.0 if (phi1 <= -2.1e-7) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(Float64(1.0 - (sin(Float64(phi2 * -0.5)) ^ 2.0)) - Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))))))); end return tmp end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
tmp = 0.0;
if (phi1 <= -2.1e-7)
tmp = R * (2.0 * atan2(sqrt((t_1 + (sin((phi1 * 0.5)) ^ 2.0))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (cos(phi1) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))));
else
tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(((1.0 - (sin((phi2 * -0.5)) ^ 2.0)) - (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0))))));
end
tmp_2 = tmp;
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi1, -2.1e-7], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)\\
\mathbf{if}\;\phi_1 \leq -2.1 \cdot 10^{-7}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_1 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_1}}{\sqrt{\left(1 - {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right) - \cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi1 < -2.1e-7Initial program 37.2%
associate-*l*37.2%
Simplified37.2%
Taylor expanded in phi2 around 0 38.3%
associate--r+38.3%
unpow238.3%
1-sub-sin38.4%
unpow238.4%
*-commutative38.4%
unpow238.4%
associate-*r*38.4%
Simplified38.4%
Taylor expanded in phi2 around 0 38.8%
if -2.1e-7 < phi1 Initial program 64.7%
associate-*l*64.7%
Simplified64.7%
Taylor expanded in phi1 around 0 54.0%
associate--r+54.0%
Simplified54.0%
Final simplification50.3%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0)))
(t_2 (sin (* (- phi1 phi2) 0.5))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt (- (/ (- 1.0 (pow t_2 4.0)) (+ 1.0 (pow t_2 2.0))) t_1)))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
double t_2 = sin(((phi1 - phi2) * 0.5));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt((((1.0 - pow(t_2, 4.0)) / (1.0 + pow(t_2, 2.0))) - t_1))));
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
t_2 = sin(((phi1 - phi2) * 0.5d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt((((1.0d0 - (t_2 ** 4.0d0)) / (1.0d0 + (t_2 ** 2.0d0))) - t_1))))
end function
assert phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
double t_2 = Math.sin(((phi1 - phi2) * 0.5));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt((((1.0 - Math.pow(t_2, 4.0)) / (1.0 + Math.pow(t_2, 2.0))) - t_1))));
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) t_2 = math.sin(((phi1 - phi2) * 0.5)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt((((1.0 - math.pow(t_2, 4.0)) / (1.0 + math.pow(t_2, 2.0))) - t_1))))
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) t_2 = sin(Float64(Float64(phi1 - phi2) * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(Float64(Float64(1.0 - (t_2 ^ 4.0)) / Float64(1.0 + (t_2 ^ 2.0))) - t_1))))) end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
t_2 = sin(((phi1 - phi2) * 0.5));
tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt((((1.0 - (t_2 ^ 4.0)) / (1.0 + (t_2 ^ 2.0))) - t_1))));
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(N[(1.0 - N[Power[t$95$2, 4.0], $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)\\
t_2 := \sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_1}}{\sqrt{\frac{1 - {t_2}^{4}}{1 + {t_2}^{2}} - t_1}}\right)
\end{array}
\end{array}
Initial program 58.0%
associate-*l*58.0%
Simplified58.1%
flip--58.1%
metadata-eval58.1%
div-inv58.1%
metadata-eval58.1%
div-inv58.1%
metadata-eval58.1%
div-inv58.1%
metadata-eval58.1%
Applied egg-rr58.1%
pow-sqr58.1%
*-commutative58.1%
metadata-eval58.1%
*-commutative58.1%
Simplified58.1%
Final simplification58.1%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0)))
(t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(* R (* 2.0 (atan2 (sqrt (+ t_2 t_1)) (sqrt (- (- 1.0 t_2) t_1)))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * atan2(sqrt((t_2 + t_1)), sqrt(((1.0 - t_2) - t_1))));
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
t_2 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt((t_2 + t_1)), sqrt(((1.0d0 - t_2) - t_1))))
end function
assert phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((t_2 + t_1)), Math.sqrt(((1.0 - t_2) - t_1))));
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) t_2 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) return R * (2.0 * math.atan2(math.sqrt((t_2 + t_1)), math.sqrt(((1.0 - t_2) - t_1))))
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) t_2 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + t_1)), sqrt(Float64(Float64(1.0 - t_2) - t_1))))) end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
t_2 = sin(((phi1 - phi2) / 2.0)) ^ 2.0;
tmp = R * (2.0 * atan2(sqrt((t_2 + t_1)), sqrt(((1.0 - t_2) - t_1))));
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$2), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_2 + t_1}}{\sqrt{\left(1 - t_2\right) - t_1}}\right)
\end{array}
\end{array}
Initial program 58.0%
associate-*l*58.0%
Simplified58.1%
Final simplification58.1%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))))
(if (<= (- lambda1 lambda2) -1.0)
(*
R
(*
2.0
(atan2
t_1
(sqrt
(-
(pow (cos (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
(*
R
(*
2.0
(atan2 t_1 (sqrt (- 1.0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))));
double tmp;
if ((lambda1 - lambda2) <= -1.0) {
tmp = R * (2.0 * atan2(t_1, sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
return tmp;
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))))
if ((lambda1 - lambda2) <= (-1.0d0)) then
tmp = r * (2.0d0 * atan2(t_1, sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (cos(phi1) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - (sin(((phi1 - phi2) * 0.5d0)) ** 2.0d0)))))
end if
code = tmp
end function
assert phi1 < phi2;
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((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0))));
double tmp;
if ((lambda1 - lambda2) <= -1.0) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (Math.cos(phi1) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - Math.pow(Math.sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
return tmp;
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))) tmp = 0 if (lambda1 - lambda2) <= -1.0: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (math.cos(phi1) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - math.pow(math.sin(((phi1 - phi2) * 0.5)), 2.0))))) return tmp
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))) tmp = 0.0 if (Float64(lambda1 - lambda2) <= -1.0) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))))); end return tmp end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
t_1 = sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))));
tmp = 0.0;
if ((lambda1 - lambda2) <= -1.0)
tmp = R * (2.0 * atan2(t_1, sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (cos(phi1) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))));
else
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - (sin(((phi1 - phi2) * 0.5)) ^ 2.0)))));
end
tmp_2 = tmp;
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -1.0], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)}\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -1:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{1 - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -1Initial program 56.5%
associate-*l*56.6%
Simplified56.6%
Taylor expanded in phi2 around 0 41.5%
associate--r+41.5%
unpow241.5%
1-sub-sin41.5%
unpow241.5%
*-commutative41.5%
unpow241.5%
associate-*r*41.5%
Simplified41.5%
if -1 < (-.f64 lambda1 lambda2) Initial program 59.0%
associate-*l*59.0%
Simplified59.0%
Taylor expanded in lambda2 around 0 41.6%
Taylor expanded in lambda1 around 0 37.5%
Final simplification39.1%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (cos phi1) (cos phi2)) (* t_1 t_1))))
(if (<= phi1 -2.1e-7)
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) t_0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_2))
(sqrt (- (pow (cos (* phi2 0.5)) 2.0) (* (cos phi2) t_0)))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1);
double tmp;
if (phi1 <= -2.1e-7) {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_2)), sqrt((pow(cos((phi2 * 0.5)), 2.0) - (cos(phi2) * t_0)))));
}
return tmp;
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
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) * (lambda2 - lambda1))) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1)
if (phi1 <= (-2.1d-7)) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (cos(phi1) * t_0)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_2)), sqrt(((cos((phi2 * 0.5d0)) ** 2.0d0) - (cos(phi2) * t_0)))))
end if
code = tmp
end function
assert phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = (Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1);
double tmp;
if (phi1 <= -2.1e-7) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (Math.cos(phi1) * t_0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_2)), Math.sqrt((Math.pow(Math.cos((phi2 * 0.5)), 2.0) - (Math.cos(phi2) * t_0)))));
}
return tmp;
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = (math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1) tmp = 0 if phi1 <= -2.1e-7: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (math.cos(phi1) * t_0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_2)), math.sqrt((math.pow(math.cos((phi2 * 0.5)), 2.0) - (math.cos(phi2) * t_0))))) return tmp
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)) tmp = 0.0 if (phi1 <= -2.1e-7) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_2)), sqrt(Float64((cos(Float64(phi2 * 0.5)) ^ 2.0) - Float64(cos(phi2) * t_0)))))); end return tmp end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin((-0.5 * (lambda2 - lambda1))) ^ 2.0;
t_1 = sin(((lambda1 - lambda2) / 2.0));
t_2 = (cos(phi1) * cos(phi2)) * (t_1 * t_1);
tmp = 0.0;
if (phi1 <= -2.1e-7)
tmp = R * (2.0 * atan2(sqrt((t_2 + (sin((phi1 * 0.5)) ^ 2.0))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (cos(phi1) * t_0)))));
else
tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_2)), sqrt(((cos((phi2 * 0.5)) ^ 2.0) - (cos(phi2) * t_0)))));
end
tmp_2 = tmp;
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi1, -2.1e-7], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_1 \cdot t_1\right)\\
\mathbf{if}\;\phi_1 \leq -2.1 \cdot 10^{-7}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_2 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_2}}{\sqrt{{\cos \left(\phi_2 \cdot 0.5\right)}^{2} - \cos \phi_2 \cdot t_0}}\right)\\
\end{array}
\end{array}
if phi1 < -2.1e-7Initial program 37.2%
associate-*l*37.2%
Simplified37.2%
Taylor expanded in phi2 around 0 38.3%
associate--r+38.3%
unpow238.3%
1-sub-sin38.4%
unpow238.4%
*-commutative38.4%
unpow238.4%
associate-*r*38.4%
Simplified38.4%
Taylor expanded in phi2 around 0 38.8%
if -2.1e-7 < phi1 Initial program 64.7%
associate-*l*64.7%
Simplified64.7%
Taylor expanded in phi1 around 0 54.0%
associate--r+54.0%
unpow254.0%
1-sub-sin54.0%
unpow254.0%
metadata-eval54.0%
associate-*r*54.0%
*-commutative54.0%
mul-1-neg54.0%
distribute-lft-neg-out54.0%
cos-neg54.0%
sub-neg54.0%
mul-1-neg54.0%
distribute-lft-in54.0%
associate-*r*54.0%
metadata-eval54.0%
metadata-eval54.0%
associate-*r*54.0%
distribute-lft-in54.0%
Simplified54.0%
Final simplification50.4%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(if (<= phi2 2.7e-18)
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (* phi1 0.5)) 2.0)))
(sqrt
(-
(pow (cos (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt (- 1.0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
double tmp;
if (phi2 <= 2.7e-18) {
tmp = R * (2.0 * atan2(sqrt((t_1 + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt((1.0 - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
return tmp;
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
if (phi2 <= 2.7d-18) then
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (cos(phi1) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt((1.0d0 - (sin(((phi1 - phi2) * 0.5d0)) ** 2.0d0)))))
end if
code = tmp
end function
assert phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
double tmp;
if (phi2 <= 2.7e-18) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (Math.cos(phi1) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt((1.0 - Math.pow(Math.sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
return tmp;
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) tmp = 0 if phi2 <= 2.7e-18: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (math.cos(phi1) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt((1.0 - math.pow(math.sin(((phi1 - phi2) * 0.5)), 2.0))))) return tmp
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) tmp = 0.0 if (phi2 <= 2.7e-18) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))))); end return tmp end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
tmp = 0.0;
if (phi2 <= 2.7e-18)
tmp = R * (2.0 * atan2(sqrt((t_1 + (sin((phi1 * 0.5)) ^ 2.0))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (cos(phi1) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0))))));
else
tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt((1.0 - (sin(((phi1 - phi2) * 0.5)) ^ 2.0)))));
end
tmp_2 = tmp;
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, 2.7e-18], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)\\
\mathbf{if}\;\phi_2 \leq 2.7 \cdot 10^{-18}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_1 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_1}}{\sqrt{1 - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi2 < 2.69999999999999989e-18Initial program 64.0%
associate-*l*64.0%
Simplified64.0%
Taylor expanded in phi2 around 0 52.1%
associate--r+52.1%
unpow252.1%
1-sub-sin52.1%
unpow252.1%
*-commutative52.1%
unpow252.1%
associate-*r*52.1%
Simplified52.1%
Taylor expanded in phi2 around 0 49.5%
if 2.69999999999999989e-18 < phi2 Initial program 42.2%
associate-*l*42.2%
Simplified42.2%
Taylor expanded in lambda2 around 0 30.0%
Taylor expanded in lambda1 around 0 26.3%
Final simplification43.2%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= lambda1 -1900000.0)
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi1)
(pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)
(pow (sin (* phi1 0.5)) 2.0)))
(sqrt
(-
(pow (cos (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* lambda1 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt (- 1.0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (lambda1 <= -1900000.0) {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi1), pow(sin((-0.5 * (lambda2 - lambda1))), 2.0), pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * pow(sin((lambda1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
return tmp;
}
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (lambda1 <= -1900000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))))); end return tmp end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda1, -1900000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\lambda_1 \leq -1900000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)}}{\sqrt{1 - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if lambda1 < -1.9e6Initial program 51.8%
associate-*l*51.9%
Simplified52.0%
Taylor expanded in phi2 around 0 37.1%
associate--r+37.1%
unpow237.1%
1-sub-sin37.1%
unpow237.1%
*-commutative37.1%
unpow237.1%
associate-*r*37.1%
Simplified37.1%
Taylor expanded in lambda2 around 0 37.1%
Taylor expanded in phi2 around 0 36.6%
+-commutative36.6%
*-commutative36.6%
fma-def36.6%
Simplified36.6%
if -1.9e6 < lambda1 Initial program 60.3%
associate-*l*60.3%
Simplified60.2%
Taylor expanded in lambda2 around 0 35.5%
Taylor expanded in lambda1 around 0 34.4%
Final simplification35.0%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= lambda1 -1900000.0)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
(sqrt
(-
(pow (cos (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* lambda1 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt (- 1.0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (lambda1 <= -1900000.0) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * pow(sin((lambda1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
return tmp;
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
if (lambda1 <= (-1900000.0d0)) then
tmp = r * (2.0d0 * atan2(sqrt(((sin((phi1 * 0.5d0)) ** 2.0d0) + (cos(phi1) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (cos(phi1) * (sin((lambda1 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0d0 - (sin(((phi1 - phi2) * 0.5d0)) ** 2.0d0)))))
end if
code = tmp
end function
assert phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (lambda1 <= -1900000.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi1 * 0.5)), 2.0) + (Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (Math.cos(phi1) * Math.pow(Math.sin((lambda1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)))), Math.sqrt((1.0 - Math.pow(Math.sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
return tmp;
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if lambda1 <= -1900000.0: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi1 * 0.5)), 2.0) + (math.cos(phi1) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (math.cos(phi1) * math.pow(math.sin((lambda1 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt((1.0 - math.pow(math.sin(((phi1 - phi2) * 0.5)), 2.0))))) return tmp
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (lambda1 <= -1900000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))))); end return tmp end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
tmp = 0.0;
if (lambda1 <= -1900000.0)
tmp = R * (2.0 * atan2(sqrt(((sin((phi1 * 0.5)) ^ 2.0) + (cos(phi1) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (cos(phi1) * (sin((lambda1 * 0.5)) ^ 2.0))))));
else
tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - (sin(((phi1 - phi2) * 0.5)) ^ 2.0)))));
end
tmp_2 = tmp;
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda1, -1900000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\lambda_1 \leq -1900000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)}}{\sqrt{1 - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if lambda1 < -1.9e6Initial program 51.8%
associate-*l*51.9%
Simplified52.0%
Taylor expanded in phi2 around 0 37.1%
associate--r+37.1%
unpow237.1%
1-sub-sin37.1%
unpow237.1%
*-commutative37.1%
unpow237.1%
associate-*r*37.1%
Simplified37.1%
Taylor expanded in lambda2 around 0 37.1%
Taylor expanded in phi2 around 0 36.6%
if -1.9e6 < lambda1 Initial program 60.3%
associate-*l*60.3%
Simplified60.2%
Taylor expanded in lambda2 around 0 35.5%
Taylor expanded in lambda1 around 0 34.4%
Final simplification35.0%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))))
(if (<= (- lambda1 lambda2) -1.0)
(*
R
(*
2.0
(atan2 t_1 (sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))))
(*
R
(*
2.0
(atan2 t_1 (sqrt (- 1.0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))));
double tmp;
if ((lambda1 - lambda2) <= -1.0) {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
return tmp;
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))))
if ((lambda1 - lambda2) <= (-1.0d0)) then
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - (sin(((phi1 - phi2) * 0.5d0)) ** 2.0d0)))))
end if
code = tmp
end function
assert phi1 < phi2;
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((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0))));
double tmp;
if ((lambda1 - lambda2) <= -1.0) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - Math.pow(Math.sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
return tmp;
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))) tmp = 0 if (lambda1 - lambda2) <= -1.0: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0))))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - math.pow(math.sin(((phi1 - phi2) * 0.5)), 2.0))))) return tmp
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))) tmp = 0.0 if (Float64(lambda1 - lambda2) <= -1.0) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))))); end return tmp end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
t_1 = sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))));
tmp = 0.0;
if ((lambda1 - lambda2) <= -1.0)
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)))));
else
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - (sin(((phi1 - phi2) * 0.5)) ^ 2.0)))));
end
tmp_2 = tmp;
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -1.0], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)}\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -1:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{1 - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -1Initial program 56.5%
associate-*l*56.6%
Simplified56.6%
Taylor expanded in phi2 around 0 35.6%
Taylor expanded in phi1 around 0 27.8%
if -1 < (-.f64 lambda1 lambda2) Initial program 59.0%
associate-*l*59.0%
Simplified59.0%
Taylor expanded in lambda2 around 0 41.6%
Taylor expanded in lambda1 around 0 37.5%
Final simplification33.5%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))))
(if (<= phi1 -400000.0)
(* R (* 2.0 (atan2 t_1 (sqrt (pow (cos (* phi1 0.5)) 2.0)))))
(*
R
(*
2.0
(atan2
t_1
(sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))));
double tmp;
if (phi1 <= -400000.0) {
tmp = R * (2.0 * atan2(t_1, sqrt(pow(cos((phi1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
return tmp;
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))))
if (phi1 <= (-400000.0d0)) then
tmp = r * (2.0d0 * atan2(t_1, sqrt((cos((phi1 * 0.5d0)) ** 2.0d0))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)))))
end if
code = tmp
end function
assert phi1 < phi2;
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((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0))));
double tmp;
if (phi1 <= -400000.0) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt(Math.pow(Math.cos((phi1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
return tmp;
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))) tmp = 0 if phi1 <= -400000.0: tmp = R * (2.0 * math.atan2(t_1, math.sqrt(math.pow(math.cos((phi1 * 0.5)), 2.0)))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0))))) return tmp
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))) tmp = 0.0 if (phi1 <= -400000.0) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt((cos(Float64(phi1 * 0.5)) ^ 2.0))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))))); end return tmp end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
t_1 = sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))));
tmp = 0.0;
if (phi1 <= -400000.0)
tmp = R * (2.0 * atan2(t_1, sqrt((cos((phi1 * 0.5)) ^ 2.0))));
else
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)))));
end
tmp_2 = tmp;
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -400000.0], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)}\\
\mathbf{if}\;\phi_1 \leq -400000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi1 < -4e5Initial program 37.3%
associate-*l*37.3%
Simplified37.3%
Taylor expanded in phi2 around 0 38.7%
associate--r+38.7%
unpow238.7%
1-sub-sin38.8%
unpow238.8%
*-commutative38.8%
unpow238.8%
associate-*r*38.8%
Simplified38.8%
Taylor expanded in lambda2 around 0 34.6%
Taylor expanded in lambda1 around 0 22.1%
if -4e5 < phi1 Initial program 64.4%
associate-*l*64.4%
Simplified64.4%
Taylor expanded in phi2 around 0 39.7%
Taylor expanded in phi1 around 0 34.5%
Final simplification31.6%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= (- lambda1 lambda2) -0.0001)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
(sqrt (pow (cos (* lambda2 -0.5)) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt (pow (cos (* phi1 0.5)) 2.0))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((lambda1 - lambda2) <= -0.0001) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + (cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))), sqrt(pow(cos((lambda2 * -0.5)), 2.0))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt(pow(cos((phi1 * 0.5)), 2.0))));
}
return tmp;
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
if ((lambda1 - lambda2) <= (-0.0001d0)) then
tmp = r * (2.0d0 * atan2(sqrt(((sin((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)))), sqrt((cos((lambda2 * (-0.5d0))) ** 2.0d0))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((cos((phi1 * 0.5d0)) ** 2.0d0))))
end if
code = tmp
end function
assert phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((lambda1 - lambda2) <= -0.0001) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))), Math.sqrt(Math.pow(Math.cos((lambda2 * -0.5)), 2.0))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)))), Math.sqrt(Math.pow(Math.cos((phi1 * 0.5)), 2.0))));
}
return tmp;
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (lambda1 - lambda2) <= -0.0001: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi2 * -0.5)), 2.0) + (math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))), math.sqrt(math.pow(math.cos((lambda2 * -0.5)), 2.0)))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt(math.pow(math.cos((phi1 * 0.5)), 2.0)))) return tmp
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (Float64(lambda1 - lambda2) <= -0.0001) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))), sqrt((cos(Float64(lambda2 * -0.5)) ^ 2.0))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt((cos(Float64(phi1 * 0.5)) ^ 2.0))))); end return tmp end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
tmp = 0.0;
if ((lambda1 - lambda2) <= -0.0001)
tmp = R * (2.0 * atan2(sqrt(((sin((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)))), sqrt((cos((lambda2 * -0.5)) ^ 2.0))));
else
tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((cos((phi1 * 0.5)) ^ 2.0))));
end
tmp_2 = tmp;
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -0.0001], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -0.0001:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\lambda_2 \cdot -0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -1.00000000000000005e-4Initial program 57.0%
associate-*l*57.0%
Simplified57.1%
Taylor expanded in phi2 around 0 36.5%
Taylor expanded in phi1 around 0 27.5%
Taylor expanded in lambda1 around 0 24.0%
unpow224.0%
1-sub-sin24.0%
unpow224.0%
Simplified24.0%
Taylor expanded in phi1 around 0 23.6%
if -1.00000000000000005e-4 < (-.f64 lambda1 lambda2) Initial program 58.8%
associate-*l*58.8%
Simplified58.8%
Taylor expanded in phi2 around 0 44.6%
associate--r+44.6%
unpow244.6%
1-sub-sin44.6%
unpow244.6%
*-commutative44.6%
unpow244.6%
associate-*r*44.6%
Simplified44.6%
Taylor expanded in lambda2 around 0 37.6%
Taylor expanded in lambda1 around 0 30.9%
Final simplification27.9%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(if (<= phi1 -0.00021)
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt (pow (cos (* phi1 0.5)) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
double tmp;
if (phi1 <= -0.00021) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt(pow(cos((phi1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_1 + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
return tmp;
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
if (phi1 <= (-0.00021d0)) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt((cos((phi1 * 0.5d0)) ** 2.0d0))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt((1.0d0 - (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)))))
end if
code = tmp
end function
assert phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
double tmp;
if (phi1 <= -0.00021) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt(Math.pow(Math.cos((phi1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
return tmp;
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) tmp = 0 if phi1 <= -0.00021: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt(math.pow(math.cos((phi1 * 0.5)), 2.0)))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((1.0 - math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0))))) return tmp
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) tmp = 0.0 if (phi1 <= -0.00021) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt((cos(Float64(phi1 * 0.5)) ^ 2.0))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))))); end return tmp end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
tmp = 0.0;
if (phi1 <= -0.00021)
tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt((cos((phi1 * 0.5)) ^ 2.0))));
else
tmp = R * (2.0 * atan2(sqrt((t_1 + (sin((phi2 * -0.5)) ^ 2.0))), sqrt((1.0 - (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)))));
end
tmp_2 = tmp;
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi1, -0.00021], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)\\
\mathbf{if}\;\phi_1 \leq -0.00021:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_1}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_1 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi1 < -2.1000000000000001e-4Initial program 37.0%
associate-*l*37.0%
Simplified37.0%
Taylor expanded in phi2 around 0 38.4%
associate--r+38.4%
unpow238.4%
1-sub-sin38.5%
unpow238.5%
*-commutative38.5%
unpow238.5%
associate-*r*38.5%
Simplified38.5%
Taylor expanded in lambda2 around 0 34.4%
Taylor expanded in lambda1 around 0 22.1%
if -2.1000000000000001e-4 < phi1 Initial program 64.6%
associate-*l*64.6%
Simplified64.6%
Taylor expanded in phi2 around 0 39.9%
Taylor expanded in phi1 around 0 34.6%
Taylor expanded in phi1 around 0 30.3%
Final simplification28.4%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))))
(if (<= phi1 -400000.0)
(* R (* 2.0 (atan2 t_1 (sqrt (pow (cos (* phi1 0.5)) 2.0)))))
(* R (* 2.0 (atan2 t_1 (sqrt (pow (cos (* lambda1 0.5)) 2.0))))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))));
double tmp;
if (phi1 <= -400000.0) {
tmp = R * (2.0 * atan2(t_1, sqrt(pow(cos((phi1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt(pow(cos((lambda1 * 0.5)), 2.0))));
}
return tmp;
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))))
if (phi1 <= (-400000.0d0)) then
tmp = r * (2.0d0 * atan2(t_1, sqrt((cos((phi1 * 0.5d0)) ** 2.0d0))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt((cos((lambda1 * 0.5d0)) ** 2.0d0))))
end if
code = tmp
end function
assert phi1 < phi2;
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((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0))));
double tmp;
if (phi1 <= -400000.0) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt(Math.pow(Math.cos((phi1 * 0.5)), 2.0))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt(Math.pow(Math.cos((lambda1 * 0.5)), 2.0))));
}
return tmp;
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))) tmp = 0 if phi1 <= -400000.0: tmp = R * (2.0 * math.atan2(t_1, math.sqrt(math.pow(math.cos((phi1 * 0.5)), 2.0)))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt(math.pow(math.cos((lambda1 * 0.5)), 2.0)))) return tmp
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))) tmp = 0.0 if (phi1 <= -400000.0) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt((cos(Float64(phi1 * 0.5)) ^ 2.0))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt((cos(Float64(lambda1 * 0.5)) ^ 2.0))))); end return tmp end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
t_1 = sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0))));
tmp = 0.0;
if (phi1 <= -400000.0)
tmp = R * (2.0 * atan2(t_1, sqrt((cos((phi1 * 0.5)) ^ 2.0))));
else
tmp = R * (2.0 * atan2(t_1, sqrt((cos((lambda1 * 0.5)) ^ 2.0))));
end
tmp_2 = tmp;
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -400000.0], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[Power[N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)}\\
\mathbf{if}\;\phi_1 \leq -400000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_1}{\sqrt{{\cos \left(\lambda_1 \cdot 0.5\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi1 < -4e5Initial program 37.3%
associate-*l*37.3%
Simplified37.3%
Taylor expanded in phi2 around 0 38.7%
associate--r+38.7%
unpow238.7%
1-sub-sin38.8%
unpow238.8%
*-commutative38.8%
unpow238.8%
associate-*r*38.8%
Simplified38.8%
Taylor expanded in lambda2 around 0 34.6%
Taylor expanded in lambda1 around 0 22.1%
if -4e5 < phi1 Initial program 64.4%
associate-*l*64.4%
Simplified64.4%
Taylor expanded in phi2 around 0 39.7%
Taylor expanded in phi1 around 0 34.5%
Taylor expanded in lambda2 around 0 29.8%
unpow229.8%
1-sub-sin29.8%
unpow229.8%
*-commutative29.8%
Simplified29.8%
Final simplification28.0%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt (pow (cos (* lambda2 -0.5)) 2.0)))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt(pow(cos((lambda2 * -0.5)), 2.0))));
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((cos((lambda2 * (-0.5d0))) ** 2.0d0))))
end function
assert phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)))), Math.sqrt(Math.pow(Math.cos((lambda2 * -0.5)), 2.0))));
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt(math.pow(math.cos((lambda2 * -0.5)), 2.0))))
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt((cos(Float64(lambda2 * -0.5)) ^ 2.0))))) end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp = code(R, lambda1, lambda2, phi1, phi2)
t_0 = sin(((lambda1 - lambda2) / 2.0));
tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((cos((lambda2 * -0.5)) ^ 2.0))));
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t_0 \cdot t_0\right)}}{\sqrt{{\cos \left(\lambda_2 \cdot -0.5\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 58.0%
associate-*l*58.0%
Simplified58.1%
Taylor expanded in phi2 around 0 37.2%
Taylor expanded in phi1 around 0 30.9%
Taylor expanded in lambda1 around 0 27.7%
unpow227.7%
1-sub-sin27.7%
unpow227.7%
Simplified27.7%
Final simplification27.7%
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
(sqrt (pow (cos (* lambda2 -0.5)) 2.0))))))assert(phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt((pow(sin((phi2 * -0.5)), 2.0) + (cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))), sqrt(pow(cos((lambda2 * -0.5)), 2.0))));
}
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function.
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt(((sin((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)))), sqrt((cos((lambda2 * (-0.5d0))) ** 2.0d0))))
end function
assert phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))), Math.sqrt(Math.pow(Math.cos((lambda2 * -0.5)), 2.0))));
}
[phi1, phi2] = sort([phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi2 * -0.5)), 2.0) + (math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))), math.sqrt(math.pow(math.cos((lambda2 * -0.5)), 2.0))))
phi1, phi2 = sort([phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))), sqrt((cos(Float64(lambda2 * -0.5)) ^ 2.0))))) end
phi1, phi2 = num2cell(sort([phi1, phi2])){:}
function tmp = code(R, lambda1, lambda2, phi1, phi2)
tmp = R * (2.0 * atan2(sqrt(((sin((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)))), sqrt((cos((lambda2 * -0.5)) ^ 2.0))));
end
NOTE: phi1 and phi2 should be sorted in increasing order before calling this function. code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
[phi1, phi2] = \mathsf{sort}([phi1, phi2])\\
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\lambda_2 \cdot -0.5\right)}^{2}}}\right)
\end{array}
Initial program 58.0%
associate-*l*58.0%
Simplified58.1%
Taylor expanded in phi2 around 0 37.2%
Taylor expanded in phi1 around 0 30.9%
Taylor expanded in lambda1 around 0 27.7%
unpow227.7%
1-sub-sin27.7%
unpow227.7%
Simplified27.7%
Taylor expanded in phi1 around 0 25.7%
Final simplification25.7%
herbie shell --seed 2023207
(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))))))))))