
(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}
Sampling outcomes in binary64 precision:
Herbie found 17 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
module fmin_fmax_functions
implicit none
private
public fmax
public fmin
interface fmax
module procedure fmax88
module procedure fmax44
module procedure fmax84
module procedure fmax48
end interface
interface fmin
module procedure fmin88
module procedure fmin44
module procedure fmin84
module procedure fmin48
end interface
contains
real(8) function fmax88(x, y) result (res)
real(8), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(x, max(x, y), y /= y), x /= x)
end function
real(4) function fmax44(x, y) result (res)
real(4), intent (in) :: x
real(4), intent (in) :: y
res = merge(y, merge(x, max(x, y), y /= y), x /= x)
end function
real(8) function fmax84(x, y) result(res)
real(8), intent (in) :: x
real(4), intent (in) :: y
res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
end function
real(8) function fmax48(x, y) result(res)
real(4), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
end function
real(8) function fmin88(x, y) result (res)
real(8), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(x, min(x, y), y /= y), x /= x)
end function
real(4) function fmin44(x, y) result (res)
real(4), intent (in) :: x
real(4), intent (in) :: y
res = merge(y, merge(x, min(x, y), y /= y), x /= x)
end function
real(8) function fmin84(x, y) result(res)
real(8), intent (in) :: x
real(4), intent (in) :: y
res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
end function
real(8) function fmin48(x, y) result(res)
real(4), intent (in) :: x
real(8), intent (in) :: y
res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
end function
end module
real(8) function code(r, lambda1, lambda2, phi1, phi2)
use fmin_fmax_functions
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* -0.5 phi2)))
(t_1 (cos (* -0.5 phi1)))
(t_2 (sin (* 0.5 phi1)))
(t_3 (cos (* -0.5 phi2)))
(t_4 (* (cos phi1) (cos phi2)))
(t_5 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
t_4
(pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)
(pow (fma t_2 t_3 (* t_0 t_1)) 2.0)))
(sqrt
(-
1.0
(+ (pow (fma t_0 t_1 (* t_3 t_2)) 2.0) (* (* t_4 t_5) t_5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((-0.5 * phi2));
double t_1 = cos((-0.5 * phi1));
double t_2 = sin((0.5 * phi1));
double t_3 = cos((-0.5 * phi2));
double t_4 = cos(phi1) * cos(phi2);
double t_5 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt(fma(t_4, pow(sin(((lambda2 - lambda1) * -0.5)), 2.0), pow(fma(t_2, t_3, (t_0 * t_1)), 2.0))), sqrt((1.0 - (pow(fma(t_0, t_1, (t_3 * t_2)), 2.0) + ((t_4 * t_5) * t_5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(-0.5 * phi2)) t_1 = cos(Float64(-0.5 * phi1)) t_2 = sin(Float64(0.5 * phi1)) t_3 = cos(Float64(-0.5 * phi2)) t_4 = Float64(cos(phi1) * cos(phi2)) t_5 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(fma(t_4, (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0), (fma(t_2, t_3, Float64(t_0 * t_1)) ^ 2.0))), sqrt(Float64(1.0 - Float64((fma(t_0, t_1, Float64(t_3 * t_2)) ^ 2.0) + Float64(Float64(t_4 * t_5) * t_5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 * N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(t$95$2 * t$95$3 + N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(t$95$0 * t$95$1 + N[(t$95$3 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$4 * t$95$5), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(-0.5 \cdot \phi_2\right)\\
t_1 := \cos \left(-0.5 \cdot \phi_1\right)\\
t_2 := \sin \left(0.5 \cdot \phi_1\right)\\
t_3 := \cos \left(-0.5 \cdot \phi_2\right)\\
t_4 := \cos \phi_1 \cdot \cos \phi_2\\
t_5 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_4, {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}, {\left(\mathsf{fma}\left(t\_2, t\_3, t\_0 \cdot t\_1\right)\right)}^{2}\right)}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(t\_0, t\_1, t\_3 \cdot t\_2\right)\right)}^{2} + \left(t\_4 \cdot t\_5\right) \cdot t\_5\right)}}\right)
\end{array}
\end{array}
Initial program 62.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6463.4
Applied rewrites63.4%
Taylor expanded in lambda1 around -inf
Applied rewrites63.5%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diff-revN/A
fp-cancel-sub-sign-invN/A
+-commutativeN/A
*-commutativeN/A
lower-fma.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-neg.f64N/A
cos-neg-revN/A
lower-cos.f64N/A
distribute-neg-frac2N/A
lower-/.f64N/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites78.2%
Taylor expanded in phi1 around inf
mul-1-negN/A
*-commutativeN/A
distribute-lft-neg-inN/A
cos-neg-revN/A
distribute-lft-neg-inN/A
metadata-evalN/A
sin-neg-revN/A
distribute-lft-neg-inN/A
metadata-evalN/A
lower-fma.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
cos-neg-revN/A
lower-cos.f64N/A
distribute-lft-neg-inN/A
metadata-evalN/A
lower-*.f64N/A
Applied rewrites78.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* -0.5 phi2)))
(t_1 (cos (* -0.5 phi1)))
(t_2 (sin (* 0.5 phi1)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (cos (* -0.5 phi2)))
(t_5
(sqrt
(fma
t_3
(pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)
(pow (fma t_2 t_4 (* t_0 t_1)) 2.0))))
(t_6 (pow (fma t_0 t_1 (* t_4 t_2)) 2.0)))
(if (or (<= lambda2 -3950000000.0) (not (<= lambda2 4.1e-44)))
(*
R
(*
2.0
(atan2
t_5
(sqrt (- 1.0 (fma t_3 (pow (sin (* -0.5 lambda2)) 2.0) t_6))))))
(*
R
(*
2.0
(atan2
t_5
(sqrt (- 1.0 (fma t_3 (pow (sin (* 0.5 lambda1)) 2.0) t_6)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((-0.5 * phi2));
double t_1 = cos((-0.5 * phi1));
double t_2 = sin((0.5 * phi1));
double t_3 = cos(phi1) * cos(phi2);
double t_4 = cos((-0.5 * phi2));
double t_5 = sqrt(fma(t_3, pow(sin(((lambda2 - lambda1) * -0.5)), 2.0), pow(fma(t_2, t_4, (t_0 * t_1)), 2.0)));
double t_6 = pow(fma(t_0, t_1, (t_4 * t_2)), 2.0);
double tmp;
if ((lambda2 <= -3950000000.0) || !(lambda2 <= 4.1e-44)) {
tmp = R * (2.0 * atan2(t_5, sqrt((1.0 - fma(t_3, pow(sin((-0.5 * lambda2)), 2.0), t_6)))));
} else {
tmp = R * (2.0 * atan2(t_5, sqrt((1.0 - fma(t_3, pow(sin((0.5 * lambda1)), 2.0), t_6)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(-0.5 * phi2)) t_1 = cos(Float64(-0.5 * phi1)) t_2 = sin(Float64(0.5 * phi1)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = cos(Float64(-0.5 * phi2)) t_5 = sqrt(fma(t_3, (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0), (fma(t_2, t_4, Float64(t_0 * t_1)) ^ 2.0))) t_6 = fma(t_0, t_1, Float64(t_4 * t_2)) ^ 2.0 tmp = 0.0 if ((lambda2 <= -3950000000.0) || !(lambda2 <= 4.1e-44)) tmp = Float64(R * Float64(2.0 * atan(t_5, sqrt(Float64(1.0 - fma(t_3, (sin(Float64(-0.5 * lambda2)) ^ 2.0), t_6)))))); else tmp = Float64(R * Float64(2.0 * atan(t_5, sqrt(Float64(1.0 - fma(t_3, (sin(Float64(0.5 * lambda1)) ^ 2.0), t_6)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Sqrt[N[(t$95$3 * N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(t$95$2 * t$95$4 + N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[Power[N[(t$95$0 * t$95$1 + N[(t$95$4 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[lambda2, -3950000000.0], N[Not[LessEqual[lambda2, 4.1e-44]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$5 / N[Sqrt[N[(1.0 - N[(t$95$3 * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$6), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$5 / N[Sqrt[N[(1.0 - N[(t$95$3 * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$6), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(-0.5 \cdot \phi_2\right)\\
t_1 := \cos \left(-0.5 \cdot \phi_1\right)\\
t_2 := \sin \left(0.5 \cdot \phi_1\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \cos \left(-0.5 \cdot \phi_2\right)\\
t_5 := \sqrt{\mathsf{fma}\left(t\_3, {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}, {\left(\mathsf{fma}\left(t\_2, t\_4, t\_0 \cdot t\_1\right)\right)}^{2}\right)}\\
t_6 := {\left(\mathsf{fma}\left(t\_0, t\_1, t\_4 \cdot t\_2\right)\right)}^{2}\\
\mathbf{if}\;\lambda_2 \leq -3950000000 \lor \neg \left(\lambda_2 \leq 4.1 \cdot 10^{-44}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_5}{\sqrt{1 - \mathsf{fma}\left(t\_3, {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, t\_6\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_5}{\sqrt{1 - \mathsf{fma}\left(t\_3, {\sin \left(0.5 \cdot \lambda_1\right)}^{2}, t\_6\right)}}\right)\\
\end{array}
\end{array}
if lambda2 < -3.95e9 or 4.09999999999999992e-44 < lambda2 Initial program 50.3%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6451.6
Applied rewrites51.6%
Taylor expanded in lambda1 around -inf
Applied rewrites51.6%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diff-revN/A
fp-cancel-sub-sign-invN/A
+-commutativeN/A
*-commutativeN/A
lower-fma.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-neg.f64N/A
cos-neg-revN/A
lower-cos.f64N/A
distribute-neg-frac2N/A
lower-/.f64N/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites61.4%
Taylor expanded in lambda1 around 0
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower-pow.f64N/A
Applied rewrites61.4%
if -3.95e9 < lambda2 < 4.09999999999999992e-44Initial program 75.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6477.1
Applied rewrites77.1%
Taylor expanded in lambda1 around -inf
Applied rewrites77.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diff-revN/A
fp-cancel-sub-sign-invN/A
+-commutativeN/A
*-commutativeN/A
lower-fma.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-neg.f64N/A
cos-neg-revN/A
lower-cos.f64N/A
distribute-neg-frac2N/A
lower-/.f64N/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites97.6%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower-pow.f64N/A
Applied rewrites97.0%
Final simplification78.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* -0.5 phi2)))
(t_2 (cos (* -0.5 phi1)))
(t_3 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0))
(t_4 (sin (* 0.5 phi1)))
(t_5 (cos (* -0.5 phi2)))
(t_6 (pow (fma t_1 t_2 (* t_5 t_4)) 2.0))
(t_7 (pow (fma t_4 t_5 (* t_1 t_2)) 2.0))
(t_8 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= lambda1 -1.5e-7)
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (pow (sin (* 0.5 lambda1)) 2.0) t_7))
(sqrt
(-
1.0
(+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (* t_0 t_8) t_8)))))))
(if (<= lambda1 5.4e-6)
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 t_3 t_7))
(sqrt (- 1.0 (fma t_0 (pow (sin (* -0.5 lambda2)) 2.0) t_6))))))
(*
(* 2.0 R)
(atan2
(sqrt (fma t_0 t_3 (pow (sin (* (- phi2 phi1) -0.5)) 2.0)))
(sqrt (- 1.0 (fma t_0 t_3 t_6)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((-0.5 * phi2));
double t_2 = cos((-0.5 * phi1));
double t_3 = pow(sin(((lambda2 - lambda1) * -0.5)), 2.0);
double t_4 = sin((0.5 * phi1));
double t_5 = cos((-0.5 * phi2));
double t_6 = pow(fma(t_1, t_2, (t_5 * t_4)), 2.0);
double t_7 = pow(fma(t_4, t_5, (t_1 * t_2)), 2.0);
double t_8 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (lambda1 <= -1.5e-7) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, pow(sin((0.5 * lambda1)), 2.0), t_7)), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_0 * t_8) * t_8))))));
} else if (lambda1 <= 5.4e-6) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, t_3, t_7)), sqrt((1.0 - fma(t_0, pow(sin((-0.5 * lambda2)), 2.0), t_6)))));
} else {
tmp = (2.0 * R) * atan2(sqrt(fma(t_0, t_3, pow(sin(((phi2 - phi1) * -0.5)), 2.0))), sqrt((1.0 - fma(t_0, t_3, t_6))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(-0.5 * phi2)) t_2 = cos(Float64(-0.5 * phi1)) t_3 = sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0 t_4 = sin(Float64(0.5 * phi1)) t_5 = cos(Float64(-0.5 * phi2)) t_6 = fma(t_1, t_2, Float64(t_5 * t_4)) ^ 2.0 t_7 = fma(t_4, t_5, Float64(t_1 * t_2)) ^ 2.0 t_8 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (lambda1 <= -1.5e-7) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, (sin(Float64(0.5 * lambda1)) ^ 2.0), t_7)), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_0 * t_8) * t_8))))))); elseif (lambda1 <= 5.4e-6) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, t_3, t_7)), sqrt(Float64(1.0 - fma(t_0, (sin(Float64(-0.5 * lambda2)) ^ 2.0), t_6)))))); else tmp = Float64(Float64(2.0 * R) * atan(sqrt(fma(t_0, t_3, (sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_0, t_3, t_6))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[Power[N[(t$95$1 * t$95$2 + N[(t$95$5 * t$95$4), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$7 = N[Power[N[(t$95$4 * t$95$5 + N[(t$95$1 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$8 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda1, -1.5e-7], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$7), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$0 * t$95$8), $MachinePrecision] * t$95$8), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 5.4e-6], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * t$95$3 + t$95$7), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$6), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$0 * t$95$3 + N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * t$95$3 + t$95$6), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(-0.5 \cdot \phi_2\right)\\
t_2 := \cos \left(-0.5 \cdot \phi_1\right)\\
t_3 := {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}\\
t_4 := \sin \left(0.5 \cdot \phi_1\right)\\
t_5 := \cos \left(-0.5 \cdot \phi_2\right)\\
t_6 := {\left(\mathsf{fma}\left(t\_1, t\_2, t\_5 \cdot t\_4\right)\right)}^{2}\\
t_7 := {\left(\mathsf{fma}\left(t\_4, t\_5, t\_1 \cdot t\_2\right)\right)}^{2}\\
t_8 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\lambda_1 \leq -1.5 \cdot 10^{-7}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, {\sin \left(0.5 \cdot \lambda_1\right)}^{2}, t\_7\right)}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_0 \cdot t\_8\right) \cdot t\_8\right)}}\right)\\
\mathbf{elif}\;\lambda_1 \leq 5.4 \cdot 10^{-6}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, t\_3, t\_7\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, t\_6\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, t\_3, {\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, t\_3, t\_6\right)}}\\
\end{array}
\end{array}
if lambda1 < -1.4999999999999999e-7Initial program 52.6%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6454.1
Applied rewrites54.1%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower-pow.f64N/A
Applied rewrites54.2%
if -1.4999999999999999e-7 < lambda1 < 5.39999999999999997e-6Initial program 77.5%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6478.8
Applied rewrites78.8%
Taylor expanded in lambda1 around -inf
Applied rewrites78.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diff-revN/A
fp-cancel-sub-sign-invN/A
+-commutativeN/A
*-commutativeN/A
lower-fma.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-neg.f64N/A
cos-neg-revN/A
lower-cos.f64N/A
distribute-neg-frac2N/A
lower-/.f64N/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites97.9%
Taylor expanded in lambda1 around 0
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower-pow.f64N/A
Applied rewrites97.9%
if 5.39999999999999997e-6 < lambda1 Initial program 43.5%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6444.7
Applied rewrites44.7%
Taylor expanded in phi1 around 0
lower-sin.f64N/A
lower-*.f6440.2
Applied rewrites40.2%
Taylor expanded in lambda1 around -inf
Applied rewrites44.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(* (cos phi1) (cos phi2))
(pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)
(pow
(fma
(sin (* -0.5 phi2))
(cos (* -0.5 phi1))
(* (cos (* -0.5 phi2)) (sin (* 0.5 phi1))))
2.0))))
(* R (* (atan2 (sqrt t_0) (sqrt (- 1.0 t_0))) 2.0))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma((cos(phi1) * cos(phi2)), pow(sin(((lambda2 - lambda1) * -0.5)), 2.0), pow(fma(sin((-0.5 * phi2)), cos((-0.5 * phi1)), (cos((-0.5 * phi2)) * sin((0.5 * phi1)))), 2.0));
return R * (atan2(sqrt(t_0), sqrt((1.0 - t_0))) * 2.0);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0), (fma(sin(Float64(-0.5 * phi2)), cos(Float64(-0.5 * phi1)), Float64(cos(Float64(-0.5 * phi2)) * sin(Float64(0.5 * phi1)))) ^ 2.0)) return Float64(R * Float64(atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))) * 2.0)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}, {\left(\mathsf{fma}\left(\sin \left(-0.5 \cdot \phi_2\right), \cos \left(-0.5 \cdot \phi_1\right), \cos \left(-0.5 \cdot \phi_2\right) \cdot \sin \left(0.5 \cdot \phi_1\right)\right)\right)}^{2}\right)\\
R \cdot \left(\tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}} \cdot 2\right)
\end{array}
\end{array}
Initial program 62.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6463.4
Applied rewrites63.4%
Taylor expanded in lambda1 around -inf
Applied rewrites63.5%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diff-revN/A
fp-cancel-sub-sign-invN/A
+-commutativeN/A
*-commutativeN/A
lower-fma.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-neg.f64N/A
cos-neg-revN/A
lower-cos.f64N/A
distribute-neg-frac2N/A
lower-/.f64N/A
metadata-evalN/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites78.2%
Taylor expanded in lambda1 around -inf
Applied rewrites78.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0))
(t_1 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
t_1
t_0
(pow
(fma
(sin (* 0.5 phi1))
(cos (* -0.5 phi2))
(* (sin (* -0.5 phi2)) (cos (* -0.5 phi1))))
2.0)))
(sqrt (- 1.0 (fma t_1 t_0 (pow (sin (* (- phi2 phi1) -0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda2 - lambda1) * -0.5)), 2.0);
double t_1 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(fma(t_1, t_0, pow(fma(sin((0.5 * phi1)), cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * cos((-0.5 * phi1)))), 2.0))), sqrt((1.0 - fma(t_1, t_0, pow(sin(((phi2 - phi1) * -0.5)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0 t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(fma(t_1, t_0, (fma(sin(Float64(0.5 * phi1)), cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(-0.5 * phi1)))) ^ 2.0))), sqrt(Float64(1.0 - fma(t_1, t_0, (sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$0 + N[Power[N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * t$95$0 + N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0, {\left(\mathsf{fma}\left(\sin \left(0.5 \cdot \phi_1\right), \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(-0.5 \cdot \phi_1\right)\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1, t\_0, {\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 62.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6463.4
Applied rewrites63.4%
Taylor expanded in lambda1 around -inf
Applied rewrites63.5%
Taylor expanded in lambda1 around -inf
Applied rewrites63.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+ t_1 (/ (* t_0 (+ (cos (- phi2 phi1)) (cos (+ phi2 phi1)))) 2.0)))
(sqrt (- (- 1.0 (* t_0 (* (cos phi2) (cos phi1)))) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) / 2.0)), 2.0);
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * atan2(sqrt((t_1 + ((t_0 * (cos((phi2 - phi1)) + cos((phi2 + phi1)))) / 2.0))), sqrt(((1.0 - (t_0 * (cos(phi2) * cos(phi1)))) - 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)) ** 2.0d0
t_1 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt((t_1 + ((t_0 * (cos((phi2 - phi1)) + cos((phi2 + phi1)))) / 2.0d0))), sqrt(((1.0d0 - (t_0 * (cos(phi2) * cos(phi1)))) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin(((lambda1 - lambda2) / 2.0)), 2.0);
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + ((t_0 * (Math.cos((phi2 - phi1)) + Math.cos((phi2 + phi1)))) / 2.0))), Math.sqrt(((1.0 - (t_0 * (Math.cos(phi2) * Math.cos(phi1)))) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((lambda1 - lambda2) / 2.0)), 2.0) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) return R * (2.0 * math.atan2(math.sqrt((t_1 + ((t_0 * (math.cos((phi2 - phi1)) + math.cos((phi2 + phi1)))) / 2.0))), math.sqrt(((1.0 - (t_0 * (math.cos(phi2) * math.cos(phi1)))) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0 t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(Float64(t_0 * Float64(cos(Float64(phi2 - phi1)) + cos(Float64(phi2 + phi1)))) / 2.0))), sqrt(Float64(Float64(1.0 - Float64(t_0 * Float64(cos(phi2) * cos(phi1)))) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)) ^ 2.0; t_1 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = R * (2.0 * atan2(sqrt((t_1 + ((t_0 * (cos((phi2 - phi1)) + cos((phi2 + phi1)))) / 2.0))), sqrt(((1.0 - (t_0 * (cos(phi2) * cos(phi1)))) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(N[(t$95$0 * N[(N[Cos[N[(phi2 - phi1), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi2 + phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2}\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \frac{t\_0 \cdot \left(\cos \left(\phi_2 - \phi_1\right) + \cos \left(\phi_2 + \phi_1\right)\right)}{2}}}{\sqrt{\left(1 - t\_0 \cdot \left(\cos \phi_2 \cdot \cos \phi_1\right)\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.1%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites62.2%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
unpow2N/A
lift-pow.f64N/A
*-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-cos.f64N/A
lift-cos.f64N/A
cos-multN/A
associate-*r/N/A
lower-/.f64N/A
Applied rewrites63.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0)))
(*
(atan2
(sqrt (fma t_1 t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (pow (cos (/ (- phi1 phi2) -2.0)) 2.0) (* t_1 t_0))))
(* R 2.0))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * cos(phi1);
double t_1 = pow(sin(((lambda1 - lambda2) / 2.0)), 2.0);
return atan2(sqrt(fma(t_1, t_0, pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (t_1 * t_0)))) * (R * 2.0);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * cos(phi1)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0 return Float64(atan(sqrt(fma(t_1, t_0, (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64(t_1 * t_0)))) * Float64(R * 2.0)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$0 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \cos \phi_1\\
t_1 := {\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2}\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}{\sqrt{{\cos \left(\frac{\phi_1 - \phi_2}{-2}\right)}^{2} - t\_1 \cdot t\_0}} \cdot \left(R \cdot 2\right)
\end{array}
\end{array}
Initial program 62.1%
Applied rewrites62.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(* (cos phi2) (cos phi1))
(pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)
(pow (sin (* (- phi2 phi1) -0.5)) 2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma((cos(phi2) * cos(phi1)), pow(sin(((lambda2 - lambda1) * -0.5)), 2.0), pow(sin(((phi2 - phi1) * -0.5)), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(Float64(cos(phi2) * cos(phi1)), (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0), (sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}, {\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.1%
Taylor expanded in lambda1 around 0
Applied rewrites62.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (or (<= phi1 -1.4e+26) (not (<= phi1 24.0)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0)))
(sqrt
(-
(pow (cos (* -0.5 phi1)) 2.0)
(* (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0) (cos phi1)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_0 (cos phi2))))
(sqrt
(-
(-
1.0
(*
(pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0)
(* (cos phi2) (cos phi1))))
t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi1 <= -1.4e+26) || !(phi1 <= 24.0)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (pow(sin(((lambda2 - lambda1) * -0.5)), 2.0) * cos(phi1))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * cos(phi2)))), sqrt(((1.0 - (pow(sin(((lambda1 - lambda2) / 2.0)), 2.0) * (cos(phi2) * cos(phi1)))) - t_1))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if ((phi1 <= -1.4e+26) || !(phi1 <= 24.0)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64((sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0) * cos(phi1))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * cos(phi2)))), sqrt(Float64(Float64(1.0 - Float64((sin(Float64(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0) * Float64(cos(phi2) * cos(phi1)))) - t_1))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -1.4e+26], N[Not[LessEqual[phi1, 24.0]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -1.4 \cdot 10^{+26} \lor \neg \left(\phi_1 \leq 24\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2} \cdot \cos \phi_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \cos \phi_2}}{\sqrt{\left(1 - {\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2} \cdot \left(\cos \phi_2 \cdot \cos \phi_1\right)\right) - t\_1}}\right)\\
\end{array}
\end{array}
if phi1 < -1.4e26 or 24 < phi1 Initial program 45.6%
Taylor expanded in phi2 around 0
Applied rewrites40.3%
Taylor expanded in phi1 around 0
Applied rewrites19.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6420.9
Applied rewrites20.9%
Taylor expanded in phi2 around 0
Applied rewrites47.6%
if -1.4e26 < phi1 < 24Initial program 76.7%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites76.8%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f6476.9
Applied rewrites76.9%
Final simplification63.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (or (<= phi2 -3.8e-6) (not (<= phi2 5.4e-6)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
(-
1.0
(*
(pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0)
(* (cos phi2) (cos phi1))))
t_1)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_0 (cos phi1))))
(sqrt
(-
(pow (cos (* -0.5 phi1)) 2.0)
(* (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0) (cos phi1))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi2 <= -3.8e-6) || !(phi2 <= 5.4e-6)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt(((1.0 - (pow(sin(((lambda1 - lambda2) / 2.0)), 2.0) * (cos(phi2) * cos(phi1)))) - t_1))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * cos(phi1)))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (pow(sin(((lambda2 - lambda1) * -0.5)), 2.0) * cos(phi1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if ((phi2 <= -3.8e-6) || !(phi2 <= 5.4e-6)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64((sin(Float64(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0) * Float64(cos(phi2) * cos(phi1)))) - t_1))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * cos(phi1)))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64((sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0) * cos(phi1))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -3.8e-6], N[Not[LessEqual[phi2, 5.4e-6]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -3.8 \cdot 10^{-6} \lor \neg \left(\phi_2 \leq 5.4 \cdot 10^{-6}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{\left(1 - {\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2} \cdot \left(\cos \phi_2 \cdot \cos \phi_1\right)\right) - t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \cos \phi_1}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2} \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if phi2 < -3.8e-6 or 5.39999999999999997e-6 < phi2 Initial program 47.3%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites47.3%
Taylor expanded in phi1 around 0
*-commutativeN/A
unpow2N/A
metadata-evalN/A
distribute-lft-neg-inN/A
metadata-evalN/A
distribute-lft-neg-inN/A
sin-neg-revN/A
sin-neg-revN/A
sqr-neg-revN/A
unpow2N/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
unpow2N/A
sqr-neg-revN/A
Applied rewrites49.2%
if -3.8e-6 < phi2 < 5.39999999999999997e-6Initial program 77.0%
Taylor expanded in phi2 around 0
Applied rewrites77.0%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f6477.0
Applied rewrites77.0%
Final simplification63.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi2 -0.00017) (not (<= phi2 0.00058)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi2) (cos phi1))
(pow (sin (* 0.5 lambda1)) 2.0)
(pow (sin (* (- phi2 phi1) -0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (cos phi1))))
(sqrt
(-
(pow (cos (* -0.5 phi1)) 2.0)
(* (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0) (cos phi1))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi2 <= -0.00017) || !(phi2 <= 0.00058)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - fma((cos(phi2) * cos(phi1)), pow(sin((0.5 * lambda1)), 2.0), pow(sin(((phi2 - phi1) * -0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * cos(phi1)))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (pow(sin(((lambda2 - lambda1) * -0.5)), 2.0) * cos(phi1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi2 <= -0.00017) || !(phi2 <= 0.00058)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi2) * cos(phi1)), (sin(Float64(0.5 * lambda1)) ^ 2.0), (sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * cos(phi1)))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64((sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0) * cos(phi1))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.00017], N[Not[LessEqual[phi2, 0.00058]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -0.00017 \lor \neg \left(\phi_2 \leq 0.00058\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, {\sin \left(0.5 \cdot \lambda_1\right)}^{2}, {\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\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} + t\_0 \cdot \cos \phi_1}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2} \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if phi2 < -1.7e-4 or 5.8e-4 < phi2 Initial program 47.1%
Taylor expanded in lambda2 around 0
Applied rewrites36.5%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6438.5
Applied rewrites38.5%
if -1.7e-4 < phi2 < 5.8e-4Initial program 76.7%
Taylor expanded in phi2 around 0
Applied rewrites76.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f6476.6
Applied rewrites76.6%
Final simplification57.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0) (cos phi1))))
(sqrt
(-
(pow (cos (* -0.5 phi1)) 2.0)
(* (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0) (cos phi1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (pow(sin((0.5 * (lambda1 - lambda2))), 2.0) * cos(phi1)))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (pow(sin(((lambda2 - lambda1) * -0.5)), 2.0) * cos(phi1))))));
}
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
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0) * cos(phi1)))), sqrt(((cos(((-0.5d0) * phi1)) ** 2.0d0) - ((sin(((lambda2 - lambda1) * (-0.5d0))) ** 2.0d0) * cos(phi1))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0) * Math.cos(phi1)))), Math.sqrt((Math.pow(Math.cos((-0.5 * phi1)), 2.0) - (Math.pow(Math.sin(((lambda2 - lambda1) * -0.5)), 2.0) * Math.cos(phi1))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) * math.cos(phi1)))), math.sqrt((math.pow(math.cos((-0.5 * phi1)), 2.0) - (math.pow(math.sin(((lambda2 - lambda1) * -0.5)), 2.0) * math.cos(phi1))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0) * cos(phi1)))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64((sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0) * cos(phi1))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((sin((0.5 * (lambda1 - lambda2))) ^ 2.0) * cos(phi1)))), sqrt(((cos((-0.5 * phi1)) ^ 2.0) - ((sin(((lambda2 - lambda1) * -0.5)) ^ 2.0) * cos(phi1)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := 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[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} \cdot \cos \phi_1}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2} \cdot \cos \phi_1}}\right)
\end{array}
Initial program 62.1%
Taylor expanded in phi2 around 0
Applied rewrites48.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f6448.7
Applied rewrites48.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(cos phi1)
(pow (sin (* 0.5 phi1)) 2.0)))
(sqrt
(-
(pow (cos (* -0.5 phi1)) 2.0)
(* (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0) (cos phi1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (pow(sin(((lambda2 - lambda1) * -0.5)), 2.0) * cos(phi1))))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64((sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0) * cos(phi1))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2} \cdot \cos \phi_1}}\right)
\end{array}
Initial program 62.1%
Taylor expanded in phi2 around 0
Applied rewrites43.4%
Taylor expanded in phi1 around 0
Applied rewrites35.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6434.8
Applied rewrites34.8%
Taylor expanded in phi2 around 0
Applied rewrites47.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi1)
(* (cos phi2) (pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(fma(cos(phi1), (cos(phi2) * pow(sin(((lambda1 - lambda2) / 2.0)), 2.0)), pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin(((lambda2 - lambda1) * -0.5)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0)), (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot {\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2}, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}}}\right)
\end{array}
Initial program 62.1%
Taylor expanded in phi2 around 0
Applied rewrites43.4%
Taylor expanded in phi1 around 0
Applied rewrites35.9%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
lift-*.f64N/A
associate-*l*N/A
lower-fma.f64N/A
Applied rewrites35.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(sqrt
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(cos phi1)
(pow (sin (* 0.5 phi1)) 2.0)))))
(if (or (<= lambda2 -3950000000.0) (not (<= lambda2 7.6e-61)))
(* R (* 2.0 (atan2 t_0 (sqrt (- 1.0 (pow (sin (* -0.5 lambda2)) 2.0))))))
(*
R
(* 2.0 (atan2 t_0 (sqrt (- 1.0 (pow (sin (* 0.5 lambda1)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sqrt(fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), cos(phi1), pow(sin((0.5 * phi1)), 2.0)));
double tmp;
if ((lambda2 <= -3950000000.0) || !(lambda2 <= 7.6e-61)) {
tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - pow(sin((-0.5 * lambda2)), 2.0)))));
} else {
tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - pow(sin((0.5 * lambda1)), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt(fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))) tmp = 0.0 if ((lambda2 <= -3950000000.0) || !(lambda2 <= 7.6e-61)) tmp = Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - (sin(Float64(-0.5 * lambda2)) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - (sin(Float64(0.5 * lambda1)) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda2, -3950000000.0], N[Not[LessEqual[lambda2, 7.6e-61]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{\mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}\\
\mathbf{if}\;\lambda_2 \leq -3950000000 \lor \neg \left(\lambda_2 \leq 7.6 \cdot 10^{-61}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - {\sin \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)\\
\end{array}
\end{array}
if lambda2 < -3.95e9 or 7.59999999999999961e-61 < lambda2 Initial program 50.8%
Taylor expanded in phi2 around 0
Applied rewrites33.5%
Taylor expanded in phi1 around 0
Applied rewrites28.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6428.2
Applied rewrites28.2%
Taylor expanded in lambda1 around 0
Applied rewrites28.4%
if -3.95e9 < lambda2 < 7.59999999999999961e-61Initial program 76.7%
Taylor expanded in phi2 around 0
Applied rewrites56.2%
Taylor expanded in phi1 around 0
Applied rewrites45.3%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6443.2
Applied rewrites43.2%
Taylor expanded in lambda2 around 0
Applied rewrites42.9%
Final simplification34.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(cos phi1)
(pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- 1.0 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((1.0 - pow(sin(((lambda2 - lambda1) * -0.5)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}}}\right)
\end{array}
Initial program 62.1%
Taylor expanded in phi2 around 0
Applied rewrites43.4%
Taylor expanded in phi1 around 0
Applied rewrites35.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6434.8
Applied rewrites34.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(cos phi1)
(pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- 1.0 (pow (sin (* -0.5 lambda2)) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((1.0 - pow(sin((-0.5 * lambda2)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(-0.5 * lambda2)) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}}}\right)
\end{array}
Initial program 62.1%
Taylor expanded in phi2 around 0
Applied rewrites43.4%
Taylor expanded in phi1 around 0
Applied rewrites35.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6434.8
Applied rewrites34.8%
Taylor expanded in lambda1 around 0
Applied rewrites28.7%
herbie shell --seed 2025003
(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))))))))))