
(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 24 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}
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (* (cos phi1) (cos phi2)) t_1) t_1)))
(if (<= phi2 1.06e-27)
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_2))
(sqrt
(-
(- 1.0 (* (cos phi1) t_0))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (* phi2 (- (* 0.5 (/ phi1 phi2)) 0.5))) 2.0) t_2))
(sqrt (- 1.0 (fma (cos phi2) t_0 (pow (sin (* -0.5 phi2)) 2.0))))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = ((cos(phi1) * cos(phi2)) * t_1) * t_1;
double tmp;
if (phi2 <= 1.06e-27) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_2)), sqrt(((1.0 - (cos(phi1) * t_0)) - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi2 * ((0.5 * (phi1 / phi2)) - 0.5))), 2.0) + t_2)), sqrt((1.0 - fma(cos(phi2), t_0, pow(sin((-0.5 * phi2)), 2.0))))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_1) * t_1) tmp = 0.0 if (phi2 <= 1.06e-27) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_2)), sqrt(Float64(Float64(1.0 - Float64(cos(phi1) * t_0)) - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi2 * Float64(Float64(0.5 * Float64(phi1 / phi2)) - 0.5))) ^ 2.0) + t_2)), sqrt(Float64(1.0 - fma(cos(phi2), t_0, (sin(Float64(-0.5 * phi2)) ^ 2.0))))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]}, If[LessEqual[phi2, 1.06e-27], 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[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi2 * N[(N[(0.5 * N[(phi1 / phi2), $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot t\_1\\
\mathbf{if}\;\phi_2 \leq 1.06 \cdot 10^{-27}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_2}}{\sqrt{\left(1 - \cos \phi_1 \cdot t\_0\right) - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot \left(0.5 \cdot \frac{\phi_1}{\phi_2} - 0.5\right)\right)}^{2} + t\_2}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_2, t\_0, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < 1.05999999999999998e-27Initial program 61.6%
Applied rewrites61.6%
Taylor expanded in phi2 around 0
lower--.f64N/A
lower-*.f64N/A
lift-cos.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6451.3
Applied rewrites51.3%
if 1.05999999999999998e-27 < phi2 Initial program 61.6%
Applied rewrites61.6%
Taylor expanded in phi1 around 0
lower--.f64N/A
lower-fma.f64N/A
lift-cos.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.4
Applied rewrites48.4%
Taylor expanded in phi2 around inf
lower-*.f64N/A
lower--.f64N/A
lower-*.f64N/A
lower-/.f6445.6
Applied rewrites45.6%
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_1) t_1)))))
(if (<= phi2 1.06e-27)
(*
R
(*
2.0
(atan2
t_2
(sqrt
(-
(- 1.0 (* (cos phi1) t_0))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(*
R
(*
2.0
(atan2
t_2
(sqrt (- 1.0 (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0))))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_1) * t_1)));
double tmp;
if (phi2 <= 1.06e-27) {
tmp = R * (2.0 * atan2(t_2, sqrt(((1.0 - (cos(phi1) * t_0)) - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_1) * t_1))) tmp = 0.0 if (phi2 <= 1.06e-27) tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(Float64(1.0 - Float64(cos(phi1) * t_0)) - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[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$1), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, 1.06e-27], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot t\_1}\\
\mathbf{if}\;\phi_2 \leq 1.06 \cdot 10^{-27}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{\left(1 - \cos \phi_1 \cdot t\_0\right) - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < 1.05999999999999998e-27Initial program 61.6%
Applied rewrites61.6%
Taylor expanded in phi2 around 0
lower--.f64N/A
lower-*.f64N/A
lift-cos.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6451.3
Applied rewrites51.3%
if 1.05999999999999998e-27 < phi2 Initial program 61.6%
Taylor expanded in phi1 around 0
lower--.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites48.4%
NOTE: R, lambda1, lambda2, 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 (* 0.5 (- phi1 phi2))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (<= phi2 1.06e-27)
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 t_0 (* (* t_2 (cos phi2)) (cos phi1))))
(sqrt (- 1.0 (fma (cos phi1) t_2 (pow (sin (* 0.5 phi1)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_1) t_1)))
(sqrt (- 1.0 (fma t_2 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0))))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if (phi2 <= 1.06e-27) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, t_0, ((t_2 * cos(phi2)) * cos(phi1)))), sqrt((1.0 - fma(cos(phi1), t_2, pow(sin((0.5 * phi1)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt((1.0 - fma(t_2, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if (phi2 <= 1.06e-27) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, t_0, Float64(Float64(t_2 * cos(phi2)) * cos(phi1)))), sqrt(Float64(1.0 - fma(cos(phi1), t_2, (sin(Float64(0.5 * phi1)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt(Float64(1.0 - fma(t_2, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi2, 1.06e-27], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * t$95$0 + N[(N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$2 + N[Power[N[Sin[N[(0.5 * phi1), $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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq 1.06 \cdot 10^{-27}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, t\_0, \left(t\_2 \cdot \cos \phi_2\right) \cdot \cos \phi_1\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_2, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot t\_1}}{\sqrt{1 - \mathsf{fma}\left(t\_2, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < 1.05999999999999998e-27Initial program 61.6%
Applied rewrites61.6%
Applied rewrites61.6%
Taylor expanded in phi2 around 0
lower--.f64N/A
lower-fma.f64N/A
lift-cos.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.8
Applied rewrites48.8%
if 1.05999999999999998e-27 < phi2 Initial program 61.6%
Taylor expanded in phi1 around 0
lower--.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites48.4%
NOTE: R, lambda1, lambda2, 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 (* 0.5 (- phi1 phi2))))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (fma t_1 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0))))
(if (<= phi2 1.06e-27)
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 t_0 (* (* t_1 (cos phi2)) (cos phi1))))
(sqrt (- 1.0 (fma (cos phi1) t_1 (pow (sin (* 0.5 phi1)) 2.0)))))))
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = fma(t_1, cos(phi2), pow(sin((-0.5 * phi2)), 2.0));
double tmp;
if (phi2 <= 1.06e-27) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, t_0, ((t_1 * cos(phi2)) * cos(phi1)))), sqrt((1.0 - fma(cos(phi1), t_1, pow(sin((0.5 * phi1)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = fma(t_1, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0)) tmp = 0.0 if (phi2 <= 1.06e-27) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, t_0, Float64(Float64(t_1 * cos(phi2)) * cos(phi1)))), sqrt(Float64(1.0 - fma(cos(phi1), t_1, (sin(Float64(0.5 * phi1)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, 1.06e-27], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * t$95$0 + N[(N[(t$95$1 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $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]), $MachinePrecision]), $MachinePrecision], 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]]]]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \mathsf{fma}\left(t\_1, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
\mathbf{if}\;\phi_2 \leq 1.06 \cdot 10^{-27}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, t\_0, \left(t\_1 \cdot \cos \phi_2\right) \cdot \cos \phi_1\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\end{array}
\end{array}
if phi2 < 1.05999999999999998e-27Initial program 61.6%
Applied rewrites61.6%
Applied rewrites61.6%
Taylor expanded in phi2 around 0
lower--.f64N/A
lower-fma.f64N/A
lift-cos.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.8
Applied rewrites48.8%
if 1.05999999999999998e-27 < phi2 Initial program 61.6%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.0%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.2%
NOTE: R, lambda1, lambda2, 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 (* 0.5 (- phi1 phi2))))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (fma t_1 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(t_3 (fma t_0 t_0 (* (cos phi1) t_1))))
(if (<= phi2 1.06e-27)
(* R (* 2.0 (atan2 (sqrt t_3) (sqrt (- 1.0 t_3)))))
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = fma(t_1, cos(phi2), pow(sin((-0.5 * phi2)), 2.0));
double t_3 = fma(t_0, t_0, (cos(phi1) * t_1));
double tmp;
if (phi2 <= 1.06e-27) {
tmp = R * (2.0 * atan2(sqrt(t_3), sqrt((1.0 - t_3))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = fma(t_1, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_3 = fma(t_0, t_0, Float64(cos(phi1) * t_1)) tmp = 0.0 if (phi2 <= 1.06e-27) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_3), sqrt(Float64(1.0 - t_3))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t$95$0 * t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, 1.06e-27], 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], 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]]]]]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \mathsf{fma}\left(t\_1, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
t_3 := \mathsf{fma}\left(t\_0, t\_0, \cos \phi_1 \cdot t\_1\right)\\
\mathbf{if}\;\phi_2 \leq 1.06 \cdot 10^{-27}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3}}{\sqrt{1 - t\_3}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\end{array}
\end{array}
if phi2 < 1.05999999999999998e-27Initial program 61.6%
Applied rewrites61.6%
Applied rewrites61.6%
Taylor expanded in phi2 around 0
lower-*.f64N/A
lift-cos.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6453.1
Applied rewrites53.1%
Taylor expanded in phi2 around 0
lower-*.f64N/A
lift-cos.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6451.2
Applied rewrites51.2%
if 1.05999999999999998e-27 < phi2 Initial program 61.6%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.0%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.2%
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(t_2 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (cos phi1)))))
(if (<= phi2 1.06e-27)
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
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(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0));
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * cos(phi1));
double tmp;
if (phi2 <= 1.06e-27) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_2 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * cos(phi1))) tmp = 0.0 if (phi2 <= 1.06e-27) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, 1.06e-27], 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], 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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \cos \phi_1\\
\mathbf{if}\;\phi_2 \leq 1.06 \cdot 10^{-27}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\end{array}
\end{array}
if phi2 < 1.05999999999999998e-27Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f6453.1
Applied rewrites53.1%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f6451.2
Applied rewrites51.2%
if 1.05999999999999998e-27 < phi2 Initial program 61.6%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.0%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.2%
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(t_2 (+ (* t_0 (cos phi1)) (pow (sin (* 0.5 phi1)) 2.0))))
(if (<= phi1 -1.45e-12)
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
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(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0));
double t_2 = (t_0 * cos(phi1)) + pow(sin((0.5 * phi1)), 2.0);
double tmp;
if (phi1 <= -1.45e-12) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_2 = Float64(Float64(t_0 * cos(phi1)) + (sin(Float64(0.5 * phi1)) ^ 2.0)) tmp = 0.0 if (phi1 <= -1.45e-12) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi1, -1.45e-12], 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], 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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
t_2 := t\_0 \cdot \cos \phi_1 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -1.45 \cdot 10^{-12}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\end{array}
\end{array}
if phi1 < -1.4500000000000001e-12Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
lift-cos.f64N/A
lift-fma.f64N/A
lift-pow.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
lift-pow.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lower-+.f64N/A
Applied rewrites46.7%
lift-cos.f64N/A
lift-fma.f64N/A
lift-pow.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
lift-pow.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lower-+.f64N/A
Applied rewrites46.7%
if -1.4500000000000001e-12 < phi1 Initial program 61.6%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.0%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.2%
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(t_2 (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0))))
(if (<= phi1 -1.45e-12)
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
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(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0));
double t_2 = fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0));
double tmp;
if (phi1 <= -1.45e-12) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_2 = fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0)) tmp = 0.0 if (phi1 <= -1.45e-12) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi1, -1.45e-12], 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], 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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
t_2 := \mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
\mathbf{if}\;\phi_1 \leq -1.45 \cdot 10^{-12}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\end{array}
\end{array}
if phi1 < -1.4500000000000001e-12Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
if -1.4500000000000001e-12 < phi1 Initial program 61.6%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.0%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.2%
NOTE: R, lambda1, lambda2, 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
(-
(- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(*
(* (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0) (cos phi2))
(cos phi1)))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && 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(((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)) - ((pow(sin((0.5 * (lambda1 - lambda2))), 2.0) * cos(phi2)) * cos(phi1))))));
}
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
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
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(((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)) - (((sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0) * cos(phi2)) * cos(phi1))))))
end function
assert R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && 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(((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)) - ((Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0) * Math.cos(phi2)) * Math.cos(phi1))))));
}
[R, lambda1, lambda2, phi1, phi2] = sort([R, lambda1, lambda2, 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(((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)) - ((math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) * math.cos(phi2)) * math.cos(phi1))))))
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, 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(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(Float64(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) - Float64(Float64((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0) * cos(phi2)) * cos(phi1))))))) end
R, lambda1, lambda2, phi1, phi2 = num2cell(sort([R, lambda1, lambda2, 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(((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0)) - (((sin((0.5 * (lambda1 - lambda2))) ^ 2.0) * cos(phi2)) * cos(phi1))))));
end
NOTE: R, lambda1, lambda2, 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, 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(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0}}{\sqrt{\left(1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) - \left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} \cdot \cos \phi_2\right) \cdot \cos \phi_1}}\right)
\end{array}
\end{array}
Initial program 61.6%
Applied rewrites61.6%
NOTE: R, lambda1, lambda2, 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
(-
(-
1.0
(*
(* (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0) (cos phi2))
(cos phi1)))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && 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(((1.0 - ((pow(sin((0.5 * (lambda1 - lambda2))), 2.0) * cos(phi2)) * cos(phi1))) - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
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
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(((1.0d0 - (((sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0) * cos(phi2)) * cos(phi1))) - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)))))
end function
assert R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && 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(((1.0 - ((Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0) * Math.cos(phi2)) * Math.cos(phi1))) - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
[R, lambda1, lambda2, phi1, phi2] = sort([R, lambda1, lambda2, 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(((1.0 - ((math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) * math.cos(phi2)) * math.cos(phi1))) - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)))))
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, 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(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(Float64(Float64(1.0 - Float64(Float64((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0) * cos(phi2)) * cos(phi1))) - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
R, lambda1, lambda2, phi1, phi2 = num2cell(sort([R, lambda1, lambda2, 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(((1.0 - (((sin((0.5 * (lambda1 - lambda2))) ^ 2.0) * cos(phi2)) * cos(phi1))) - (sin((0.5 * (phi1 - phi2))) ^ 2.0)))));
end
NOTE: R, lambda1, lambda2, 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, 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(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0}}{\sqrt{\left(1 - \left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} \cdot \cos \phi_2\right) \cdot \cos \phi_1\right) - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 61.6%
Applied rewrites61.6%
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(* (cos phi2) (cos phi1))
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma((cos(phi2) * cos(phi1)), pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow(sin((0.5 * (phi1 - phi2))), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(Float64(cos(phi2) * cos(phi1)), (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_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 61.6%
Applied rewrites61.6%
Applied rewrites61.6%
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0))))
(if (<= phi1 -950.0)
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_1) t_1)))
(sqrt (- 1.0 t_0))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0));
double tmp;
if (phi1 <= -950.0) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt((1.0 - t_0))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0)) tmp = 0.0 if (phi1 <= -950.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt(Float64(1.0 - t_0))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi1, -950.0], 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], 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
\mathbf{if}\;\phi_1 \leq -950:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot t\_1}}{\sqrt{1 - t\_0}}\right)\\
\end{array}
\end{array}
if phi1 < -950Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
if -950 < phi1 Initial program 61.6%
Applied rewrites61.6%
Taylor expanded in phi1 around 0
lower--.f64N/A
lower-fma.f64N/A
lift-cos.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.4
Applied rewrites48.4%
Taylor expanded in phi2 around 0
lower--.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6435.1
Applied rewrites35.1%
NOTE: R, lambda1, lambda2, 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
(fma
(pow (sin (* -0.5 lambda2)) 2.0)
(cos phi1)
(pow (sin (* 0.5 phi1)) 2.0))))
(if (<= phi1 -950.0)
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))
(*
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 (* 0.5 (- lambda1 lambda2))) 2.0)))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && 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 = fma(pow(sin((-0.5 * lambda2)), 2.0), cos(phi1), pow(sin((0.5 * phi1)), 2.0));
double tmp;
if (phi1 <= -950.0) {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
} 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((0.5 * (lambda1 - lambda2))), 2.0)))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = fma((sin(Float64(-0.5 * lambda2)) ^ 2.0), cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0)) tmp = 0.0 if (phi1 <= -950.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi1, -950.0], 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], 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * 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]]]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \mathsf{fma}\left({\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
\mathbf{if}\;\phi_1 \leq -950:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\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}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if phi1 < -950Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
Taylor expanded in lambda1 around 0
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6434.1
Applied rewrites34.1%
Taylor expanded in lambda1 around 0
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6433.9
Applied rewrites33.9%
if -950 < phi1 Initial program 61.6%
Applied rewrites61.6%
Taylor expanded in phi1 around 0
lower--.f64N/A
lower-fma.f64N/A
lift-cos.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.4
Applied rewrites48.4%
Taylor expanded in phi2 around 0
lower--.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6435.1
Applied rewrites35.1%
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (fma t_0 1.0 (pow (sin (* 0.5 phi1)) 2.0))))
(if (<= phi2 3.4e-103)
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_1) t_1)))
(sqrt (- 1.0 t_0))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = fma(t_0, 1.0, pow(sin((0.5 * phi1)), 2.0));
double tmp;
if (phi2 <= 3.4e-103) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt((1.0 - t_0))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = fma(t_0, 1.0, (sin(Float64(0.5 * phi1)) ^ 2.0)) tmp = 0.0 if (phi2 <= 3.4e-103) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt(Float64(1.0 - t_0))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$0 * 1.0 + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, 3.4e-103], 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], 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \mathsf{fma}\left(t\_0, 1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)\\
\mathbf{if}\;\phi_2 \leq 3.4 \cdot 10^{-103}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot t\_1}}{\sqrt{1 - t\_0}}\right)\\
\end{array}
\end{array}
if phi2 < 3.40000000000000003e-103Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
Taylor expanded in phi1 around 0
Applied rewrites37.8%
Taylor expanded in phi1 around 0
Applied rewrites33.5%
if 3.40000000000000003e-103 < phi2 Initial program 61.6%
Applied rewrites61.6%
Taylor expanded in phi1 around 0
lower--.f64N/A
lower-fma.f64N/A
lift-cos.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.4
Applied rewrites48.4%
Taylor expanded in phi2 around 0
lower--.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6435.1
Applied rewrites35.1%
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
1.0
(pow (sin (* 0.5 phi1)) 2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), 1.0, pow(sin((0.5 * phi1)), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), 1.0, (sin(Float64(0.5 * phi1)) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * 1.0 + 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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, 1, {\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 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
Taylor expanded in phi1 around 0
Applied rewrites37.8%
Taylor expanded in phi1 around 0
Applied rewrites33.5%
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(cos phi1)
(* 0.25 (* phi1 phi1)))))
(* R (* 2.0 (atan2 (sqrt t_0) (pow (- 1.0 t_0) 0.5))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), cos(phi1), (0.25 * (phi1 * phi1)));
return R * (2.0 * atan2(sqrt(t_0), pow((1.0 - t_0), 0.5)));
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), cos(phi1), Float64(0.25 * Float64(phi1 * phi1))) return Float64(R * Float64(2.0 * atan(sqrt(t_0), (Float64(1.0 - t_0) ^ 0.5)))) end
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[(0.25 * N[(phi1 * phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Power[N[(1.0 - t$95$0), $MachinePrecision], 0.5], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, \cos \phi_1, 0.25 \cdot \left(\phi_1 \cdot \phi_1\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{{\left(1 - t\_0\right)}^{0.5}}\right)
\end{array}
\end{array}
Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
Taylor expanded in phi1 around 0
lower-*.f64N/A
unpow2N/A
lower-*.f6432.0
Applied rewrites32.0%
Taylor expanded in phi1 around 0
lower-*.f64N/A
unpow2N/A
lower-*.f6422.4
Applied rewrites22.4%
lift-sqrt.f64N/A
pow1/2N/A
lower-pow.f6427.6
Applied rewrites27.6%
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (fma t_0 (cos phi1) (* 0.25 (* phi1 phi1))))
(t_2 (fma -0.5 (* phi1 phi2) t_0)))
(if (<= phi1 -950.0)
(* R (* 2.0 (atan2 (sqrt t_2) (pow (- 1.0 t_2) 0.5))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
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(t_0, cos(phi1), (0.25 * (phi1 * phi1)));
double t_2 = fma(-0.5, (phi1 * phi2), t_0);
double tmp;
if (phi1 <= -950.0) {
tmp = R * (2.0 * atan2(sqrt(t_2), pow((1.0 - t_2), 0.5)));
} else {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = fma(t_0, cos(phi1), Float64(0.25 * Float64(phi1 * phi1))) t_2 = fma(-0.5, Float64(phi1 * phi2), t_0) tmp = 0.0 if (phi1 <= -950.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), (Float64(1.0 - t_2) ^ 0.5)))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[(0.25 * N[(phi1 * phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(-0.5 * N[(phi1 * phi2), $MachinePrecision] + t$95$0), $MachinePrecision]}, If[LessEqual[phi1, -950.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Power[N[(1.0 - t$95$2), $MachinePrecision], 0.5], $MachinePrecision]], $MachinePrecision]), $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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \mathsf{fma}\left(t\_0, \cos \phi_1, 0.25 \cdot \left(\phi_1 \cdot \phi_1\right)\right)\\
t_2 := \mathsf{fma}\left(-0.5, \phi_1 \cdot \phi_2, t\_0\right)\\
\mathbf{if}\;\phi_1 \leq -950:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{{\left(1 - t\_2\right)}^{0.5}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\end{array}
\end{array}
if phi1 < -950Initial program 61.6%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites42.4%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites39.0%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6423.6
Applied rewrites23.6%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6420.9
Applied rewrites20.9%
lift-sqrt.f64N/A
pow1/2N/A
lower-pow.f6422.3
Applied rewrites22.3%
if -950 < phi1 Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
Taylor expanded in phi1 around 0
lower-*.f64N/A
unpow2N/A
lower-*.f6432.0
Applied rewrites32.0%
Taylor expanded in phi1 around 0
lower-*.f64N/A
unpow2N/A
lower-*.f6422.4
Applied rewrites22.4%
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (fma t_0 (+ 1.0 (* -0.5 (* phi1 phi1))) (* 0.25 (* phi1 phi1))))
(t_2 (fma -0.5 (* phi1 phi2) t_0)))
(if (<= phi1 -950.0)
(* R (* 2.0 (atan2 (sqrt t_2) (pow (- 1.0 t_2) 0.5))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
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(t_0, (1.0 + (-0.5 * (phi1 * phi1))), (0.25 * (phi1 * phi1)));
double t_2 = fma(-0.5, (phi1 * phi2), t_0);
double tmp;
if (phi1 <= -950.0) {
tmp = R * (2.0 * atan2(sqrt(t_2), pow((1.0 - t_2), 0.5)));
} else {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = fma(t_0, Float64(1.0 + Float64(-0.5 * Float64(phi1 * phi1))), Float64(0.25 * Float64(phi1 * phi1))) t_2 = fma(-0.5, Float64(phi1 * phi2), t_0) tmp = 0.0 if (phi1 <= -950.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), (Float64(1.0 - t_2) ^ 0.5)))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(1.0 + N[(-0.5 * N[(phi1 * phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.25 * N[(phi1 * phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(-0.5 * N[(phi1 * phi2), $MachinePrecision] + t$95$0), $MachinePrecision]}, If[LessEqual[phi1, -950.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Power[N[(1.0 - t$95$2), $MachinePrecision], 0.5], $MachinePrecision]], $MachinePrecision]), $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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \mathsf{fma}\left(t\_0, 1 + -0.5 \cdot \left(\phi_1 \cdot \phi_1\right), 0.25 \cdot \left(\phi_1 \cdot \phi_1\right)\right)\\
t_2 := \mathsf{fma}\left(-0.5, \phi_1 \cdot \phi_2, t\_0\right)\\
\mathbf{if}\;\phi_1 \leq -950:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{{\left(1 - t\_2\right)}^{0.5}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\end{array}
\end{array}
if phi1 < -950Initial program 61.6%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites42.4%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites39.0%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6423.6
Applied rewrites23.6%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6420.9
Applied rewrites20.9%
lift-sqrt.f64N/A
pow1/2N/A
lower-pow.f6422.3
Applied rewrites22.3%
if -950 < phi1 Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
Taylor expanded in phi1 around 0
lower-*.f64N/A
unpow2N/A
lower-*.f6432.0
Applied rewrites32.0%
Taylor expanded in phi1 around 0
lower-*.f64N/A
unpow2N/A
lower-*.f6422.4
Applied rewrites22.4%
Taylor expanded in phi1 around 0
lower-+.f64N/A
lower-*.f64N/A
pow2N/A
lift-*.f6422.4
Applied rewrites22.4%
Taylor expanded in phi1 around 0
lower-+.f64N/A
lower-*.f64N/A
pow2N/A
lift-*.f6422.4
Applied rewrites22.4%
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (fma t_0 1.0 (* 0.25 (* phi1 phi1))))
(t_2 (fma -0.5 (* phi1 phi2) t_0)))
(if (<= phi1 -950.0)
(* R (* 2.0 (atan2 (sqrt t_2) (pow (- 1.0 t_2) 0.5))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
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(t_0, 1.0, (0.25 * (phi1 * phi1)));
double t_2 = fma(-0.5, (phi1 * phi2), t_0);
double tmp;
if (phi1 <= -950.0) {
tmp = R * (2.0 * atan2(sqrt(t_2), pow((1.0 - t_2), 0.5)));
} else {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = fma(t_0, 1.0, Float64(0.25 * Float64(phi1 * phi1))) t_2 = fma(-0.5, Float64(phi1 * phi2), t_0) tmp = 0.0 if (phi1 <= -950.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), (Float64(1.0 - t_2) ^ 0.5)))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * 1.0 + N[(0.25 * N[(phi1 * phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(-0.5 * N[(phi1 * phi2), $MachinePrecision] + t$95$0), $MachinePrecision]}, If[LessEqual[phi1, -950.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Power[N[(1.0 - t$95$2), $MachinePrecision], 0.5], $MachinePrecision]], $MachinePrecision]), $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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \mathsf{fma}\left(t\_0, 1, 0.25 \cdot \left(\phi_1 \cdot \phi_1\right)\right)\\
t_2 := \mathsf{fma}\left(-0.5, \phi_1 \cdot \phi_2, t\_0\right)\\
\mathbf{if}\;\phi_1 \leq -950:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{{\left(1 - t\_2\right)}^{0.5}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\end{array}
\end{array}
if phi1 < -950Initial program 61.6%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites42.4%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites39.0%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6423.6
Applied rewrites23.6%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6420.9
Applied rewrites20.9%
lift-sqrt.f64N/A
pow1/2N/A
lower-pow.f6422.3
Applied rewrites22.3%
if -950 < phi1 Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
Taylor expanded in phi1 around 0
lower-*.f64N/A
unpow2N/A
lower-*.f6432.0
Applied rewrites32.0%
Taylor expanded in phi1 around 0
lower-*.f64N/A
unpow2N/A
lower-*.f6422.4
Applied rewrites22.4%
Taylor expanded in phi1 around 0
Applied rewrites22.3%
Taylor expanded in phi1 around 0
Applied rewrites22.3%
NOTE: R, lambda1, lambda2, 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 (- lambda1 lambda2))) 2.0))
(t_1 (fma t_0 1.0 (* 0.25 (* phi1 phi1))))
(t_2 (fma -0.5 (* phi1 phi2) t_0)))
(if (<= phi1 -950.0)
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1))))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
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(t_0, 1.0, (0.25 * (phi1 * phi1)));
double t_2 = fma(-0.5, (phi1 * phi2), t_0);
double tmp;
if (phi1 <= -950.0) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = fma(t_0, 1.0, Float64(0.25 * Float64(phi1 * phi1))) t_2 = fma(-0.5, Float64(phi1 * phi2), t_0) tmp = 0.0 if (phi1 <= -950.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); end return tmp end
NOTE: R, lambda1, lambda2, 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[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * 1.0 + N[(0.25 * N[(phi1 * phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(-0.5 * N[(phi1 * phi2), $MachinePrecision] + t$95$0), $MachinePrecision]}, If[LessEqual[phi1, -950.0], 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], 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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \mathsf{fma}\left(t\_0, 1, 0.25 \cdot \left(\phi_1 \cdot \phi_1\right)\right)\\
t_2 := \mathsf{fma}\left(-0.5, \phi_1 \cdot \phi_2, t\_0\right)\\
\mathbf{if}\;\phi_1 \leq -950:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\end{array}
\end{array}
if phi1 < -950Initial program 61.6%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites42.4%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites39.0%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6423.6
Applied rewrites23.6%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6420.9
Applied rewrites20.9%
if -950 < phi1 Initial program 61.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
metadata-evalN/A
mult-flipN/A
lower-pow.f64N/A
lower-sin.f64N/A
mult-flipN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
lift--.f64N/A
lift-cos.f64N/A
lower-pow.f64N/A
Applied rewrites46.7%
Taylor expanded in phi1 around 0
lower-*.f64N/A
unpow2N/A
lower-*.f6432.0
Applied rewrites32.0%
Taylor expanded in phi1 around 0
lower-*.f64N/A
unpow2N/A
lower-*.f6422.4
Applied rewrites22.4%
Taylor expanded in phi1 around 0
Applied rewrites22.3%
Taylor expanded in phi1 around 0
Applied rewrites22.3%
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma -0.5 (* phi1 phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(-0.5, (phi1 * phi2), pow(sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(-0.5, Float64(phi1 * phi2), (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(-0.5 * N[(phi1 * phi2), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(-0.5, \phi_1 \cdot \phi_2, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_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 61.6%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites42.4%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites39.0%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6423.6
Applied rewrites23.6%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6420.9
Applied rewrites20.9%
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (fma -0.5 (* phi1 phi2) (pow (sin (* 0.5 lambda1)) 2.0)))
(t_1 (fma -0.5 (* phi1 phi2) (pow (sin (* -0.5 lambda2)) 2.0)))
(t_2 (* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
(if (<= lambda2 -8e-95)
t_2
(if (<= lambda2 4.2e-60)
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))
t_2))))assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(-0.5, (phi1 * phi2), pow(sin((0.5 * lambda1)), 2.0));
double t_1 = fma(-0.5, (phi1 * phi2), pow(sin((-0.5 * lambda2)), 2.0));
double t_2 = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
double tmp;
if (lambda2 <= -8e-95) {
tmp = t_2;
} else if (lambda2 <= 4.2e-60) {
tmp = R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
} else {
tmp = t_2;
}
return tmp;
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(-0.5, Float64(phi1 * phi2), (sin(Float64(0.5 * lambda1)) ^ 2.0)) t_1 = fma(-0.5, Float64(phi1 * phi2), (sin(Float64(-0.5 * lambda2)) ^ 2.0)) t_2 = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) tmp = 0.0 if (lambda2 <= -8e-95) tmp = t_2; elseif (lambda2 <= 4.2e-60) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))); else tmp = t_2; end return tmp end
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(-0.5 * N[(phi1 * phi2), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(-0.5 * N[(phi1 * phi2), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * lambda2), $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[lambda2, -8e-95], t$95$2, If[LessEqual[lambda2, 4.2e-60], 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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(-0.5, \phi_1 \cdot \phi_2, {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right)\\
t_1 := \mathsf{fma}\left(-0.5, \phi_1 \cdot \phi_2, {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}\right)\\
t_2 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{if}\;\lambda_2 \leq -8 \cdot 10^{-95}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\lambda_2 \leq 4.2 \cdot 10^{-60}:\\
\;\;\;\;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 lambda2 < -7.99999999999999992e-95 or 4.19999999999999982e-60 < lambda2 Initial program 61.6%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites42.4%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites39.0%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6423.6
Applied rewrites23.6%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6420.9
Applied rewrites20.9%
Taylor expanded in lambda1 around 0
lower-*.f6412.8
Applied rewrites12.8%
Taylor expanded in lambda1 around 0
lower-*.f6412.8
Applied rewrites12.8%
if -7.99999999999999992e-95 < lambda2 < 4.19999999999999982e-60Initial program 61.6%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites42.4%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites39.0%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6423.6
Applied rewrites23.6%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6420.9
Applied rewrites20.9%
Taylor expanded in lambda2 around 0
lower-pow.f64N/A
lift-sin.f64N/A
lift-*.f6412.6
Applied rewrites12.6%
Taylor expanded in lambda2 around 0
lower-pow.f64N/A
lift-sin.f64N/A
lift-*.f6412.6
Applied rewrites12.6%
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function. (FPCore (R lambda1 lambda2 phi1 phi2) :precision binary64 (let* ((t_0 (fma -0.5 (* phi1 phi2) (pow (sin (* 0.5 lambda1)) 2.0)))) (* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(-0.5, (phi1 * phi2), pow(sin((0.5 * lambda1)), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(-0.5, Float64(phi1 * phi2), (sin(Float64(0.5 * lambda1)) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(-0.5 * N[(phi1 * phi2), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * lambda1), $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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(-0.5, \phi_1 \cdot \phi_2, {\sin \left(0.5 \cdot \lambda_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 61.6%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites42.4%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites39.0%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6423.6
Applied rewrites23.6%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6420.9
Applied rewrites20.9%
Taylor expanded in lambda2 around 0
lower-pow.f64N/A
lift-sin.f64N/A
lift-*.f6412.6
Applied rewrites12.6%
Taylor expanded in lambda2 around 0
lower-pow.f64N/A
lift-sin.f64N/A
lift-*.f6412.6
Applied rewrites12.6%
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function. (FPCore (R lambda1 lambda2 phi1 phi2) :precision binary64 (let* ((t_0 (* -0.5 (* phi1 phi2)))) (* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
assert(R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2);
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = -0.5 * (phi1 * phi2);
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
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
t_0 = (-0.5d0) * (phi1 * phi2)
code = r * (2.0d0 * atan2(sqrt(t_0), sqrt((1.0d0 - t_0))))
end function
assert R < lambda1 && lambda1 < lambda2 && lambda2 < phi1 && phi1 < phi2;
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = -0.5 * (phi1 * phi2);
return R * (2.0 * Math.atan2(Math.sqrt(t_0), Math.sqrt((1.0 - t_0))));
}
[R, lambda1, lambda2, phi1, phi2] = sort([R, lambda1, lambda2, phi1, phi2]) def code(R, lambda1, lambda2, phi1, phi2): t_0 = -0.5 * (phi1 * phi2) return R * (2.0 * math.atan2(math.sqrt(t_0), math.sqrt((1.0 - t_0))))
R, lambda1, lambda2, phi1, phi2 = sort([R, lambda1, lambda2, phi1, phi2]) function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(-0.5 * Float64(phi1 * phi2)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
R, lambda1, lambda2, phi1, phi2 = num2cell(sort([R, lambda1, lambda2, phi1, phi2])){:}
function tmp = code(R, lambda1, lambda2, phi1, phi2)
t_0 = -0.5 * (phi1 * phi2);
tmp = R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
end
NOTE: R, lambda1, lambda2, phi1, and phi2 should be sorted in increasing order before calling this function.
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(-0.5 * N[(phi1 * phi2), $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}
[R, lambda1, lambda2, phi1, phi2] = \mathsf{sort}([R, lambda1, lambda2, phi1, phi2])\\
\\
\begin{array}{l}
t_0 := -0.5 \cdot \left(\phi_1 \cdot \phi_2\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 61.6%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites42.4%
Taylor expanded in phi1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-fma.f64N/A
Applied rewrites39.0%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6423.6
Applied rewrites23.6%
Taylor expanded in phi2 around 0
lower-fma.f64N/A
lower-*.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f6420.9
Applied rewrites20.9%
Taylor expanded in phi1 around inf
lower-*.f64N/A
lift-*.f642.2
Applied rewrites2.2%
Taylor expanded in phi1 around inf
lower-*.f64N/A
lift-*.f642.2
Applied rewrites2.2%
herbie shell --seed 2025134
(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))))))))))