
(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))));
}
module fmin_fmax_functions
implicit none
private
public fmax
public fmin
interface fmax
module procedure fmax88
module procedure fmax44
module procedure fmax84
module procedure fmax48
end interface
interface fmin
module procedure fmin88
module procedure fmin44
module procedure fmin84
module procedure fmin48
end interface
contains
real(8) function fmax88(x, y) result (res)
real(8), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(x, max(x, y), y /= y), x /= x)
end function
real(4) function fmax44(x, y) result (res)
real(4), intent (in) :: x
real(4), intent (in) :: y
res = merge(y, merge(x, max(x, y), y /= y), x /= x)
end function
real(8) function fmax84(x, y) result(res)
real(8), intent (in) :: x
real(4), intent (in) :: y
res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
end function
real(8) function fmax48(x, y) result(res)
real(4), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
end function
real(8) function fmin88(x, y) result (res)
real(8), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(x, min(x, y), y /= y), x /= x)
end function
real(4) function fmin44(x, y) result (res)
real(4), intent (in) :: x
real(4), intent (in) :: y
res = merge(y, merge(x, min(x, y), y /= y), x /= x)
end function
real(8) function fmin84(x, y) result(res)
real(8), intent (in) :: x
real(4), intent (in) :: y
res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
end function
real(8) function fmin48(x, y) result(res)
real(4), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
end function
end module
real(8) function code(r, lambda1, lambda2, phi1, phi2)
use fmin_fmax_functions
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}
Herbie found 17 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))));
}
module fmin_fmax_functions
implicit none
private
public fmax
public fmin
interface fmax
module procedure fmax88
module procedure fmax44
module procedure fmax84
module procedure fmax48
end interface
interface fmin
module procedure fmin88
module procedure fmin44
module procedure fmin84
module procedure fmin48
end interface
contains
real(8) function fmax88(x, y) result (res)
real(8), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(x, max(x, y), y /= y), x /= x)
end function
real(4) function fmax44(x, y) result (res)
real(4), intent (in) :: x
real(4), intent (in) :: y
res = merge(y, merge(x, max(x, y), y /= y), x /= x)
end function
real(8) function fmax84(x, y) result(res)
real(8), intent (in) :: x
real(4), intent (in) :: y
res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
end function
real(8) function fmax48(x, y) result(res)
real(4), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
end function
real(8) function fmin88(x, y) result (res)
real(8), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(x, min(x, y), y /= y), x /= x)
end function
real(4) function fmin44(x, y) result (res)
real(4), intent (in) :: x
real(4), intent (in) :: y
res = merge(y, merge(x, min(x, y), y /= y), x /= x)
end function
real(8) function fmin84(x, y) result(res)
real(8), intent (in) :: x
real(4), intent (in) :: y
res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
end function
real(8) function fmin48(x, y) result(res)
real(4), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
end function
end module
real(8) function code(r, lambda1, lambda2, phi1, phi2)
use fmin_fmax_functions
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (pow t_0 2.0))
(t_2 (sin (* 0.5 phi1)))
(t_3 (fma (cos phi2) t_1 (pow (sin (* -0.5 phi2)) 2.0)))
(t_4 (* R (* 2.0 (atan2 (sqrt t_3) (sqrt (- 1.0 t_3)))))))
(if (<= phi2 -8.5e-12)
t_4
(if (<= phi2 0.0027)
(*
(*
(atan2
(sqrt
(fma
(* (cos phi1) t_0)
(sin (* (- lambda1 lambda2) 0.5))
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt
(-
(+ 1.0 (* phi2 (* (cos (* 0.5 phi1)) t_2)))
(fma (cos phi1) t_1 (pow t_2 2.0)))))
2.0)
R)
t_4))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = pow(t_0, 2.0);
double t_2 = sin((0.5 * phi1));
double t_3 = fma(cos(phi2), t_1, pow(sin((-0.5 * phi2)), 2.0));
double t_4 = R * (2.0 * atan2(sqrt(t_3), sqrt((1.0 - t_3))));
double tmp;
if (phi2 <= -8.5e-12) {
tmp = t_4;
} else if (phi2 <= 0.0027) {
tmp = (atan2(sqrt(fma((cos(phi1) * t_0), sin(((lambda1 - lambda2) * 0.5)), pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt(((1.0 + (phi2 * (cos((0.5 * phi1)) * t_2))) - fma(cos(phi1), t_1, pow(t_2, 2.0))))) * 2.0) * R;
} else {
tmp = t_4;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = t_0 ^ 2.0 t_2 = sin(Float64(0.5 * phi1)) t_3 = fma(cos(phi2), t_1, (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_4 = Float64(R * Float64(2.0 * atan(sqrt(t_3), sqrt(Float64(1.0 - t_3))))) tmp = 0.0 if (phi2 <= -8.5e-12) tmp = t_4; elseif (phi2 <= 0.0027) tmp = Float64(Float64(atan(sqrt(fma(Float64(cos(phi1) * t_0), sin(Float64(Float64(lambda1 - lambda2) * 0.5)), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(Float64(1.0 + Float64(phi2 * Float64(cos(Float64(0.5 * phi1)) * t_2))) - fma(cos(phi1), t_1, (t_2 ^ 2.0))))) * 2.0) * R); else tmp = t_4; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[t$95$0, 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi2], $MachinePrecision] * t$95$1 + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$3], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, -8.5e-12], t$95$4, If[LessEqual[phi2, 0.0027], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] * N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(phi2 * N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$1 + N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$4]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := {t\_0}^{2}\\
t_2 := \sin \left(0.5 \cdot \phi_1\right)\\
t_3 := \mathsf{fma}\left(\cos \phi_2, t\_1, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
t_4 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3}}{\sqrt{1 - t\_3}}\right)\\
\mathbf{if}\;\phi_2 \leq -8.5 \cdot 10^{-12}:\\
\;\;\;\;t\_4\\
\mathbf{elif}\;\phi_2 \leq 0.0027:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot t\_0, \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right), {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{\left(1 + \phi_2 \cdot \left(\cos \left(0.5 \cdot \phi_1\right) \cdot t\_2\right)\right) - \mathsf{fma}\left(\cos \phi_1, t\_1, {t\_2}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_4\\
\end{array}
\end{array}
if phi2 < -8.4999999999999997e-12 or 0.0027000000000000001 < phi2 Initial program 62.2%
Taylor expanded in phi1 around 0
Applied rewrites46.7%
Taylor expanded in phi1 around 0
Applied rewrites46.8%
if -8.4999999999999997e-12 < phi2 < 0.0027000000000000001Initial program 62.2%
Applied rewrites62.2%
Taylor expanded in phi2 around 0
Applied rewrites52.9%
Taylor expanded in phi2 around 0
Applied rewrites50.7%
Taylor expanded in phi2 around 0
Applied rewrites42.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5)))
(t_1
(fma
(cos phi1)
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow (sin (* 0.5 phi1)) 2.0)))
(t_2 (sqrt (- 1.0 t_1)))
(t_3 (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(t_4 (fma (* (cos phi2) t_0) t_0 t_3)))
(if (<= phi1 -2.1e-5)
(* R (* 2.0 (atan2 (sqrt t_1) t_2)))
(if (<= phi1 110.0)
(* (* (atan2 (sqrt t_4) (sqrt (- 1.0 t_4))) 2.0) R)
(*
(*
(atan2 (sqrt (fma (* (* (cos phi1) (cos phi2)) t_0) t_0 t_3)) t_2)
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
double t_1 = fma(cos(phi1), pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow(sin((0.5 * phi1)), 2.0));
double t_2 = sqrt((1.0 - t_1));
double t_3 = pow(sin(((phi1 - phi2) * 0.5)), 2.0);
double t_4 = fma((cos(phi2) * t_0), t_0, t_3);
double tmp;
if (phi1 <= -2.1e-5) {
tmp = R * (2.0 * atan2(sqrt(t_1), t_2));
} else if (phi1 <= 110.0) {
tmp = (atan2(sqrt(t_4), sqrt((1.0 - t_4))) * 2.0) * R;
} else {
tmp = (atan2(sqrt(fma(((cos(phi1) * cos(phi2)) * t_0), t_0, t_3)), t_2) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) t_1 = fma(cos(phi1), (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (sin(Float64(0.5 * phi1)) ^ 2.0)) t_2 = sqrt(Float64(1.0 - t_1)) t_3 = sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0 t_4 = fma(Float64(cos(phi2) * t_0), t_0, t_3) tmp = 0.0 if (phi1 <= -2.1e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), t_2))); elseif (phi1 <= 110.0) tmp = Float64(Float64(atan(sqrt(t_4), sqrt(Float64(1.0 - t_4))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(fma(Float64(Float64(cos(phi1) * cos(phi2)) * t_0), t_0, t_3)), t_2) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0 + t$95$3), $MachinePrecision]}, If[LessEqual[phi1, -2.1e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 110.0], N[(N[(N[ArcTan[N[Sqrt[t$95$4], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0 + t$95$3), $MachinePrecision]], $MachinePrecision] / t$95$2], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
t_1 := \mathsf{fma}\left(\cos \phi_1, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
t_2 := \sqrt{1 - t\_1}\\
t_3 := {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\\
t_4 := \mathsf{fma}\left(\cos \phi_2 \cdot t\_0, t\_0, t\_3\right)\\
\mathbf{if}\;\phi_1 \leq -2.1 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{t\_2}\right)\\
\mathbf{elif}\;\phi_1 \leq 110:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_4}}{\sqrt{1 - t\_4}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0, t\_0, t\_3\right)}}{t\_2} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi1 < -2.09999999999999988e-5Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
if -2.09999999999999988e-5 < phi1 < 110Initial program 62.2%
Applied rewrites62.2%
Taylor expanded in phi1 around 0
Applied rewrites53.4%
Taylor expanded in phi1 around 0
Applied rewrites51.2%
if 110 < phi1 Initial program 62.2%
Applied rewrites62.2%
Taylor expanded in phi2 around 0
Applied rewrites48.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (pow t_0 2.0))
(t_2 (fma (cos phi2) t_1 (pow (sin (* -0.5 phi2)) 2.0)))
(t_3 (* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))))
(if (<= phi2 -8.5e-12)
t_3
(if (<= phi2 0.0027)
(*
(*
(atan2
(sqrt
(fma
(* (cos phi1) t_0)
(sin (* (- lambda1 lambda2) 0.5))
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 (fma (cos phi1) t_1 (pow (sin (* 0.5 phi1)) 2.0)))))
2.0)
R)
t_3))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = pow(t_0, 2.0);
double t_2 = fma(cos(phi2), t_1, pow(sin((-0.5 * phi2)), 2.0));
double t_3 = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
double tmp;
if (phi2 <= -8.5e-12) {
tmp = t_3;
} else if (phi2 <= 0.0027) {
tmp = (atan2(sqrt(fma((cos(phi1) * t_0), sin(((lambda1 - lambda2) * 0.5)), pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - fma(cos(phi1), t_1, pow(sin((0.5 * phi1)), 2.0))))) * 2.0) * R;
} else {
tmp = t_3;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = t_0 ^ 2.0 t_2 = fma(cos(phi2), t_1, (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_3 = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))) tmp = 0.0 if (phi2 <= -8.5e-12) tmp = t_3; elseif (phi2 <= 0.0027) tmp = Float64(Float64(atan(sqrt(fma(Float64(cos(phi1) * t_0), sin(Float64(Float64(lambda1 - lambda2) * 0.5)), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(cos(phi1), t_1, (sin(Float64(0.5 * phi1)) ^ 2.0))))) * 2.0) * R); else tmp = t_3; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[t$95$0, 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi2], $MachinePrecision] * t$95$1 + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, -8.5e-12], t$95$3, If[LessEqual[phi2, 0.0027], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] * N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$1 + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$3]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := {t\_0}^{2}\\
t_2 := \mathsf{fma}\left(\cos \phi_2, t\_1, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
t_3 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{if}\;\phi_2 \leq -8.5 \cdot 10^{-12}:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\phi_2 \leq 0.0027:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot t\_0, \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right), {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if phi2 < -8.4999999999999997e-12 or 0.0027000000000000001 < phi2 Initial program 62.2%
Taylor expanded in phi1 around 0
Applied rewrites46.7%
Taylor expanded in phi1 around 0
Applied rewrites46.8%
if -8.4999999999999997e-12 < phi2 < 0.0027000000000000001Initial program 62.2%
Applied rewrites62.2%
Taylor expanded in phi2 around 0
Applied rewrites52.9%
Taylor expanded in phi2 around 0
Applied rewrites50.7%
Taylor expanded in phi2 around 0
Applied rewrites48.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (cos phi1) t_0)))
(t_2 (fma (cos phi2) t_0 (pow (sin (* -0.5 phi2)) 2.0)))
(t_3 (* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))))
(if (<= phi2 -8.5e-12)
t_3
(if (<= phi2 0.0027)
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))
t_3))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (cos(phi1) * t_0);
double t_2 = fma(cos(phi2), t_0, pow(sin((-0.5 * phi2)), 2.0));
double t_3 = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
double tmp;
if (phi2 <= -8.5e-12) {
tmp = t_3;
} else if (phi2 <= 0.0027) {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
} else {
tmp = t_3;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(cos(phi1) * t_0)) t_2 = fma(cos(phi2), t_0, (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_3 = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))) tmp = 0.0 if (phi2 <= -8.5e-12) tmp = t_3; elseif (phi2 <= 0.0027) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); else tmp = t_3; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, -8.5e-12], t$95$3, If[LessEqual[phi2, 0.0027], 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], t$95$3]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \cos \phi_1 \cdot t\_0\\
t_2 := \mathsf{fma}\left(\cos \phi_2, t\_0, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
t_3 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{if}\;\phi_2 \leq -8.5 \cdot 10^{-12}:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\phi_2 \leq 0.0027:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if phi2 < -8.4999999999999997e-12 or 0.0027000000000000001 < phi2 Initial program 62.2%
Taylor expanded in phi1 around 0
Applied rewrites46.7%
Taylor expanded in phi1 around 0
Applied rewrites46.8%
if -8.4999999999999997e-12 < phi2 < 0.0027000000000000001Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites52.9%
Taylor expanded in phi2 around 0
Applied rewrites50.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5)))
(t_1
(fma
(* (* (cos phi1) (cos phi2)) t_0)
t_0
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
(* (* (atan2 (sqrt t_1) (sqrt (- 1.0 t_1))) 2.0) R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
double t_1 = fma(((cos(phi1) * cos(phi2)) * t_0), t_0, pow(sin(((phi1 - phi2) * 0.5)), 2.0));
return (atan2(sqrt(t_1), sqrt((1.0 - t_1))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) t_1 = fma(Float64(Float64(cos(phi1) * cos(phi2)) * t_0), t_0, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)) return Float64(Float64(atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
t_1 := \mathsf{fma}\left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0, t\_0, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)\\
\left(\tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.2%
Applied rewrites62.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (fma (cos phi2) t_0 (pow (sin (* -0.5 phi2)) 2.0)))
(t_2 (fma (cos phi1) t_0 (pow (sin (* 0.5 phi1)) 2.0)))
(t_3 (* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))))
(if (<= phi1 -2.2e-50)
t_3
(if (<= phi1 1.28e-11)
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))
t_3))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = fma(cos(phi2), t_0, pow(sin((-0.5 * phi2)), 2.0));
double t_2 = fma(cos(phi1), t_0, pow(sin((0.5 * phi1)), 2.0));
double t_3 = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
double tmp;
if (phi1 <= -2.2e-50) {
tmp = t_3;
} else if (phi1 <= 1.28e-11) {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
} else {
tmp = t_3;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = fma(cos(phi2), t_0, (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_2 = fma(cos(phi1), t_0, (sin(Float64(0.5 * phi1)) ^ 2.0)) t_3 = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))) tmp = 0.0 if (phi1 <= -2.2e-50) tmp = t_3; elseif (phi1 <= 1.28e-11) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); else tmp = t_3; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi1, -2.2e-50], t$95$3, If[LessEqual[phi1, 1.28e-11], 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], t$95$3]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \mathsf{fma}\left(\cos \phi_2, t\_0, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
t_2 := \mathsf{fma}\left(\cos \phi_1, t\_0, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
t_3 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{if}\;\phi_1 \leq -2.2 \cdot 10^{-50}:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\phi_1 \leq 1.28 \cdot 10^{-11}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if phi1 < -2.1999999999999999e-50 or 1.28e-11 < phi1 Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
if -2.1999999999999999e-50 < phi1 < 1.28e-11Initial program 62.2%
Taylor expanded in phi1 around 0
Applied rewrites46.7%
Taylor expanded in phi1 around 0
Applied rewrites46.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(cos phi1)
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow (sin (* 0.5 phi1)) 2.0)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (sin (* (- lambda1 lambda2) 0.5)))
(t_3 (* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
(if (<= t_1 -0.05)
t_3
(if (<= t_1 4e-26)
(*
(*
(atan2
(sqrt
(fma
(* (* (cos phi1) (cos phi2)) t_2)
t_2
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))
2.0)
R)
t_3))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(cos(phi1), pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow(sin((0.5 * phi1)), 2.0));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sin(((lambda1 - lambda2) * 0.5));
double t_3 = R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
double tmp;
if (t_1 <= -0.05) {
tmp = t_3;
} else if (t_1 <= 4e-26) {
tmp = (atan2(sqrt(fma(((cos(phi1) * cos(phi2)) * t_2), t_2, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))) * 2.0) * R;
} else {
tmp = t_3;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(cos(phi1), (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (sin(Float64(0.5 * phi1)) ^ 2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) t_3 = Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) tmp = 0.0 if (t_1 <= -0.05) tmp = t_3; elseif (t_1 <= 4e-26) tmp = Float64(Float64(atan(sqrt(fma(Float64(Float64(cos(phi1) * cos(phi2)) * t_2), t_2, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))) * 2.0) * R); else tmp = t_3; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, -0.05], t$95$3, If[LessEqual[t$95$1, 4e-26], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] * t$95$2 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$3]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(\cos \phi_1, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
t_3 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)\\
\mathbf{if}\;t\_1 \leq -0.05:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;t\_1 \leq 4 \cdot 10^{-26}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2, t\_2, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.050000000000000003 or 4.0000000000000002e-26 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
if -0.050000000000000003 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 4.0000000000000002e-26Initial program 62.2%
Applied rewrites62.2%
Taylor expanded in lambda2 around 0
Applied rewrites42.0%
Taylor expanded in lambda1 around 0
Applied rewrites34.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 phi1)) 2.0))
(t_1 (fma (cos phi1) (pow (sin (* 0.5 lambda1)) 2.0) t_0))
(t_2 (sin (* (- lambda1 lambda2) 0.5)))
(t_3 (fma (cos phi1) (pow (sin (* -0.5 lambda2)) 2.0) t_0))
(t_4 (* R (* 2.0 (atan2 (sqrt t_3) (sqrt (- 1.0 t_3)))))))
(if (<= lambda2 -2.3e-12)
t_4
(if (<= lambda2 2.8e-145)
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))
(if (<= lambda2 0.15)
(*
(*
(atan2
(sqrt
(fma
(* (* (cos phi1) (cos phi2)) t_2)
t_2
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))
2.0)
R)
t_4)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * phi1)), 2.0);
double t_1 = fma(cos(phi1), pow(sin((0.5 * lambda1)), 2.0), t_0);
double t_2 = sin(((lambda1 - lambda2) * 0.5));
double t_3 = fma(cos(phi1), pow(sin((-0.5 * lambda2)), 2.0), t_0);
double t_4 = R * (2.0 * atan2(sqrt(t_3), sqrt((1.0 - t_3))));
double tmp;
if (lambda2 <= -2.3e-12) {
tmp = t_4;
} else if (lambda2 <= 2.8e-145) {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
} else if (lambda2 <= 0.15) {
tmp = (atan2(sqrt(fma(((cos(phi1) * cos(phi2)) * t_2), t_2, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))) * 2.0) * R;
} else {
tmp = t_4;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi1)) ^ 2.0 t_1 = fma(cos(phi1), (sin(Float64(0.5 * lambda1)) ^ 2.0), t_0) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) t_3 = fma(cos(phi1), (sin(Float64(-0.5 * lambda2)) ^ 2.0), t_0) t_4 = Float64(R * Float64(2.0 * atan(sqrt(t_3), sqrt(Float64(1.0 - t_3))))) tmp = 0.0 if (lambda2 <= -2.3e-12) tmp = t_4; elseif (lambda2 <= 2.8e-145) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); elseif (lambda2 <= 0.15) tmp = Float64(Float64(atan(sqrt(fma(Float64(Float64(cos(phi1) * cos(phi2)) * t_2), t_2, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))) * 2.0) * R); else tmp = t_4; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$0), $MachinePrecision]}, Block[{t$95$4 = N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$3], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[lambda2, -2.3e-12], t$95$4, If[LessEqual[lambda2, 2.8e-145], 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], If[LessEqual[lambda2, 0.15], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] * t$95$2 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$4]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \phi_1\right)}^{2}\\
t_1 := \mathsf{fma}\left(\cos \phi_1, {\sin \left(0.5 \cdot \lambda_1\right)}^{2}, t\_0\right)\\
t_2 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
t_3 := \mathsf{fma}\left(\cos \phi_1, {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, t\_0\right)\\
t_4 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3}}{\sqrt{1 - t\_3}}\right)\\
\mathbf{if}\;\lambda_2 \leq -2.3 \cdot 10^{-12}:\\
\;\;\;\;t\_4\\
\mathbf{elif}\;\lambda_2 \leq 2.8 \cdot 10^{-145}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{elif}\;\lambda_2 \leq 0.15:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2, t\_2, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_4\\
\end{array}
\end{array}
if lambda2 < -2.29999999999999989e-12 or 0.149999999999999994 < lambda2 Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
Taylor expanded in lambda1 around 0
Applied rewrites33.7%
Taylor expanded in lambda1 around 0
Applied rewrites33.5%
if -2.29999999999999989e-12 < lambda2 < 2.8000000000000001e-145Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
Taylor expanded in lambda2 around 0
Applied rewrites34.2%
Taylor expanded in lambda2 around 0
Applied rewrites34.1%
if 2.8000000000000001e-145 < lambda2 < 0.149999999999999994Initial program 62.2%
Applied rewrites62.2%
Taylor expanded in lambda2 around 0
Applied rewrites42.0%
Taylor expanded in lambda1 around 0
Applied rewrites34.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (sin (* (- lambda1 lambda2) 0.5)))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (* t_3 t_0) t_0))))
(if (<= t_0 -0.299)
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_4)))))
(if (<= t_0 5e-30)
(*
(*
(atan2
(sqrt (fma (* t_3 t_1) t_1 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))
2.0)
R)
(* R (* 2.0 (atan2 (sqrt t_4) (sqrt (- 1.0 t_2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sin(((lambda1 - lambda2) * 0.5));
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_3 = cos(phi1) * cos(phi2);
double t_4 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_3 * t_0) * t_0);
double tmp;
if (t_0 <= -0.299) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_4))));
} else if (t_0 <= 5e-30) {
tmp = (atan2(sqrt(fma((t_3 * t_1), t_1, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))) * 2.0) * R;
} else {
tmp = R * (2.0 * atan2(sqrt(t_4), sqrt((1.0 - t_2))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_3 * t_0) * t_0)) tmp = 0.0 if (t_0 <= -0.299) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_4))))); elseif (t_0 <= 5e-30) tmp = Float64(Float64(atan(sqrt(fma(Float64(t_3 * t_1), t_1, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))) * 2.0) * R); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_4), sqrt(Float64(1.0 - t_2))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$3 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$0, -0.299], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$0, 5e-30], N[(N[(N[ArcTan[N[Sqrt[N[(N[(t$95$3 * t$95$1), $MachinePrecision] * t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$4], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_3 \cdot t\_0\right) \cdot t\_0\\
\mathbf{if}\;t\_0 \leq -0.299:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_4}}\right)\\
\mathbf{elif}\;t\_0 \leq 5 \cdot 10^{-30}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_3 \cdot t\_1, t\_1, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4}}{\sqrt{1 - t\_2}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.298999999999999988Initial program 62.2%
Taylor expanded in phi1 around 0
Applied rewrites43.8%
Taylor expanded in phi2 around 0
Applied rewrites29.6%
if -0.298999999999999988 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 4.99999999999999972e-30Initial program 62.2%
Applied rewrites62.2%
Taylor expanded in lambda2 around 0
Applied rewrites42.0%
Taylor expanded in lambda1 around 0
Applied rewrites34.3%
if 4.99999999999999972e-30 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites42.4%
Taylor expanded in phi1 around 0
Applied rewrites34.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2
(*
R
(*
2.0
(atan2
(sqrt
(+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (* t_1 t_0) t_0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))
(t_3 (sin (* (- lambda1 lambda2) 0.5))))
(if (<= t_0 -0.299)
t_2
(if (<= t_0 5e-30)
(*
(*
(atan2
(sqrt (fma (* t_1 t_3) t_3 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))
2.0)
R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_1 * t_0) * t_0))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
double t_3 = sin(((lambda1 - lambda2) * 0.5));
double tmp;
if (t_0 <= -0.299) {
tmp = t_2;
} else if (t_0 <= 5e-30) {
tmp = (atan2(sqrt(fma((t_1 * t_3), t_3, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_1 * t_0) * t_0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))) t_3 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) tmp = 0.0 if (t_0 <= -0.299) tmp = t_2; elseif (t_0 <= 5e-30) tmp = Float64(Float64(atan(sqrt(fma(Float64(t_1 * t_3), t_3, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = 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[(t$95$1 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$0, -0.299], t$95$2, If[LessEqual[t$95$0, 5e-30], N[(N[(N[ArcTan[N[Sqrt[N[(N[(t$95$1 * t$95$3), $MachinePrecision] * t$95$3 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_1 \cdot t\_0\right) \cdot t\_0}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
t_3 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
\mathbf{if}\;t\_0 \leq -0.299:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;t\_0 \leq 5 \cdot 10^{-30}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1 \cdot t\_3, t\_3, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.298999999999999988 or 4.99999999999999972e-30 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites42.4%
Taylor expanded in phi1 around 0
Applied rewrites34.8%
if -0.298999999999999988 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 4.99999999999999972e-30Initial program 62.2%
Applied rewrites62.2%
Taylor expanded in lambda2 around 0
Applied rewrites42.0%
Taylor expanded in lambda1 around 0
Applied rewrites34.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5)))
(t_1
(*
(*
(atan2
(sqrt
(fma
(* (* (cos phi1) (cos phi2)) t_0)
t_0
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))
2.0)
R))
(t_2
(fma
1.0
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow (sin (* 0.5 phi1)) 2.0))))
(if (<= phi2 -2.46e-23)
t_1
(if (<= phi2 5e-22)
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))
t_1))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
double t_1 = (atan2(sqrt(fma(((cos(phi1) * cos(phi2)) * t_0), t_0, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))) * 2.0) * R;
double t_2 = fma(1.0, pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow(sin((0.5 * phi1)), 2.0));
double tmp;
if (phi2 <= -2.46e-23) {
tmp = t_1;
} else if (phi2 <= 5e-22) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
} else {
tmp = t_1;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) t_1 = Float64(Float64(atan(sqrt(fma(Float64(Float64(cos(phi1) * cos(phi2)) * t_0), t_0, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))) * 2.0) * R) t_2 = fma(1.0, (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (sin(Float64(0.5 * phi1)) ^ 2.0)) tmp = 0.0 if (phi2 <= -2.46e-23) tmp = t_1; elseif (phi2 <= 5e-22) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); else tmp = t_1; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, Block[{t$95$2 = N[(1.0 * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, -2.46e-23], t$95$1, If[LessEqual[phi2, 5e-22], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
t_1 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0, t\_0, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}} \cdot 2\right) \cdot R\\
t_2 := \mathsf{fma}\left(1, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
\mathbf{if}\;\phi_2 \leq -2.46 \cdot 10^{-23}:\\
\;\;\;\;t\_1\\
\mathbf{elif}\;\phi_2 \leq 5 \cdot 10^{-22}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;t\_1\\
\end{array}
\end{array}
if phi2 < -2.4599999999999999e-23 or 4.99999999999999954e-22 < phi2 Initial program 62.2%
Applied rewrites62.2%
Taylor expanded in lambda2 around 0
Applied rewrites42.0%
Taylor expanded in lambda1 around 0
Applied rewrites34.3%
if -2.4599999999999999e-23 < phi2 < 4.99999999999999954e-22Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
Taylor expanded in phi1 around 0
Applied rewrites37.5%
Taylor expanded in phi1 around 0
Applied rewrites33.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5)))
(t_1
(*
(*
(atan2
(sqrt
(fma
(* (* (cos phi1) (cos phi2)) t_0)
t_0
(pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))
2.0)
R))
(t_2
(fma
1.0
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow (sin (* 0.5 phi1)) 2.0))))
(if (<= phi2 -0.16)
t_1
(if (<= phi2 16.0)
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))
t_1))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
double t_1 = (atan2(sqrt(fma(((cos(phi1) * cos(phi2)) * t_0), t_0, pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))) * 2.0) * R;
double t_2 = fma(1.0, pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow(sin((0.5 * phi1)), 2.0));
double tmp;
if (phi2 <= -0.16) {
tmp = t_1;
} else if (phi2 <= 16.0) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
} else {
tmp = t_1;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) t_1 = Float64(Float64(atan(sqrt(fma(Float64(Float64(cos(phi1) * cos(phi2)) * t_0), t_0, (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))) * 2.0) * R) t_2 = fma(1.0, (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (sin(Float64(0.5 * phi1)) ^ 2.0)) tmp = 0.0 if (phi2 <= -0.16) tmp = t_1; elseif (phi2 <= 16.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); else tmp = t_1; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, Block[{t$95$2 = N[(1.0 * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, -0.16], t$95$1, If[LessEqual[phi2, 16.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
t_1 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0, t\_0, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}} \cdot 2\right) \cdot R\\
t_2 := \mathsf{fma}\left(1, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
\mathbf{if}\;\phi_2 \leq -0.16:\\
\;\;\;\;t\_1\\
\mathbf{elif}\;\phi_2 \leq 16:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;t\_1\\
\end{array}
\end{array}
if phi2 < -0.160000000000000003 or 16 < phi2 Initial program 62.2%
Applied rewrites62.2%
Taylor expanded in lambda2 around 0
Applied rewrites42.0%
Taylor expanded in phi1 around 0
Applied rewrites29.3%
Taylor expanded in lambda1 around 0
Applied rewrites24.9%
if -0.160000000000000003 < phi2 < 16Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
Taylor expanded in phi1 around 0
Applied rewrites37.5%
Taylor expanded in phi1 around 0
Applied rewrites33.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
1.0
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow (* 0.5 phi1) 2.0)))
(t_1
(fma
1.0
(pow (sin (* -0.5 lambda2)) 2.0)
(pow (sin (* 0.5 phi1)) 2.0)))
(t_2 (* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
(if (<= phi1 -2.05e-5)
t_2
(if (<= phi1 7.8e-32)
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(1.0, pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow((0.5 * phi1), 2.0));
double t_1 = fma(1.0, pow(sin((-0.5 * lambda2)), 2.0), pow(sin((0.5 * phi1)), 2.0));
double t_2 = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
double tmp;
if (phi1 <= -2.05e-5) {
tmp = t_2;
} else if (phi1 <= 7.8e-32) {
tmp = R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(1.0, (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (Float64(0.5 * phi1) ^ 2.0)) t_1 = fma(1.0, (sin(Float64(-0.5 * lambda2)) ^ 2.0), (sin(Float64(0.5 * phi1)) ^ 2.0)) t_2 = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) tmp = 0.0 if (phi1 <= -2.05e-5) tmp = t_2; elseif (phi1 <= 7.8e-32) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(1.0 * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(0.5 * phi1), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(1.0 * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = 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]}, If[LessEqual[phi1, -2.05e-5], t$95$2, If[LessEqual[phi1, 7.8e-32], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(1, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\left(0.5 \cdot \phi_1\right)}^{2}\right)\\
t_1 := \mathsf{fma}\left(1, {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
t_2 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{if}\;\phi_1 \leq -2.05 \cdot 10^{-5}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\phi_1 \leq 7.8 \cdot 10^{-32}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if phi1 < -2.05000000000000002e-5 or 7.8000000000000003e-32 < phi1 Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
Taylor expanded in phi1 around 0
Applied rewrites37.5%
Taylor expanded in phi1 around 0
Applied rewrites33.5%
Taylor expanded in lambda1 around 0
Applied rewrites25.2%
Taylor expanded in lambda1 around 0
Applied rewrites26.4%
if -2.05000000000000002e-5 < phi1 < 7.8000000000000003e-32Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
Taylor expanded in phi1 around 0
Applied rewrites37.5%
Taylor expanded in phi1 around 0
Applied rewrites33.5%
Taylor expanded in phi1 around 0
Applied rewrites28.2%
Taylor expanded in phi1 around 0
Applied rewrites22.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
1.0
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow (sin (* 0.5 phi1)) 2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(1.0, pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow(sin((0.5 * phi1)), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(1.0, (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (sin(Float64(0.5 * phi1)) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(1.0 * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(1, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
Taylor expanded in phi1 around 0
Applied rewrites37.5%
Taylor expanded in phi1 around 0
Applied rewrites33.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
1.0
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow
(* phi1 (+ 0.5 (* -0.020833333333333332 (pow phi1 2.0))))
2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(1.0, pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow((phi1 * (0.5 + (-0.020833333333333332 * pow(phi1, 2.0)))), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(1.0, (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (Float64(phi1 * Float64(0.5 + Float64(-0.020833333333333332 * (phi1 ^ 2.0)))) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(1.0 * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(phi1 * N[(0.5 + N[(-0.020833333333333332 * N[Power[phi1, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(1, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\left(\phi_1 \cdot \left(0.5 + -0.020833333333333332 \cdot {\phi_1}^{2}\right)\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
Taylor expanded in phi1 around 0
Applied rewrites37.5%
Taylor expanded in phi1 around 0
Applied rewrites33.5%
Taylor expanded in phi1 around 0
Applied rewrites28.2%
Taylor expanded in phi1 around 0
Applied rewrites22.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
1.0
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow (* 0.5 phi1) 2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(1.0, pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow((0.5 * phi1), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(1.0, (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (Float64(0.5 * phi1) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(1.0 * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(0.5 * phi1), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(1, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\left(0.5 \cdot \phi_1\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
Taylor expanded in phi1 around 0
Applied rewrites37.5%
Taylor expanded in phi1 around 0
Applied rewrites33.5%
Taylor expanded in phi1 around 0
Applied rewrites28.2%
Taylor expanded in phi1 around 0
Applied rewrites22.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma 1.0 (pow (sin (* -0.5 lambda2)) 2.0) (pow (* 0.5 phi1) 2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(1.0, pow(sin((-0.5 * lambda2)), 2.0), pow((0.5 * phi1), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(1.0, (sin(Float64(-0.5 * lambda2)) ^ 2.0), (Float64(0.5 * phi1) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(1.0 * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(0.5 * phi1), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(1, {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, {\left(0.5 \cdot \phi_1\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.2%
Taylor expanded in phi2 around 0
Applied rewrites46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.4%
Taylor expanded in phi1 around 0
Applied rewrites37.5%
Taylor expanded in phi1 around 0
Applied rewrites33.5%
Taylor expanded in phi1 around 0
Applied rewrites28.2%
Taylor expanded in phi1 around 0
Applied rewrites22.3%
Taylor expanded in lambda1 around 0
Applied rewrites14.2%
Taylor expanded in lambda1 around 0
Applied rewrites14.2%
herbie shell --seed 2025160
(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))))))))))