
(FPCore (F B x) :precision binary64 (+ (- (* x (/ 1.0 (tan B)))) (* (/ F (sin B)) (pow (+ (+ (* F F) 2.0) (* 2.0 x)) (- (/ 1.0 2.0))))))
double code(double F, double B, double x) {
return -(x * (1.0 / tan(B))) + ((F / sin(B)) * pow((((F * F) + 2.0) + (2.0 * x)), -(1.0 / 2.0)));
}
real(8) function code(f, b, x)
real(8), intent (in) :: f
real(8), intent (in) :: b
real(8), intent (in) :: x
code = -(x * (1.0d0 / tan(b))) + ((f / sin(b)) * ((((f * f) + 2.0d0) + (2.0d0 * x)) ** -(1.0d0 / 2.0d0)))
end function
public static double code(double F, double B, double x) {
return -(x * (1.0 / Math.tan(B))) + ((F / Math.sin(B)) * Math.pow((((F * F) + 2.0) + (2.0 * x)), -(1.0 / 2.0)));
}
def code(F, B, x): return -(x * (1.0 / math.tan(B))) + ((F / math.sin(B)) * math.pow((((F * F) + 2.0) + (2.0 * x)), -(1.0 / 2.0)))
function code(F, B, x) return Float64(Float64(-Float64(x * Float64(1.0 / tan(B)))) + Float64(Float64(F / sin(B)) * (Float64(Float64(Float64(F * F) + 2.0) + Float64(2.0 * x)) ^ Float64(-Float64(1.0 / 2.0))))) end
function tmp = code(F, B, x) tmp = -(x * (1.0 / tan(B))) + ((F / sin(B)) * ((((F * F) + 2.0) + (2.0 * x)) ^ -(1.0 / 2.0))); end
code[F_, B_, x_] := N[((-N[(x * N[(1.0 / N[Tan[B], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]) + N[(N[(F / N[Sin[B], $MachinePrecision]), $MachinePrecision] * N[Power[N[(N[(N[(F * F), $MachinePrecision] + 2.0), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision], (-N[(1.0 / 2.0), $MachinePrecision])], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(-x \cdot \frac{1}{\tan B}\right) + \frac{F}{\sin B} \cdot {\left(\left(F \cdot F + 2\right) + 2 \cdot x\right)}^{\left(-\frac{1}{2}\right)}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 25 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (F B x) :precision binary64 (+ (- (* x (/ 1.0 (tan B)))) (* (/ F (sin B)) (pow (+ (+ (* F F) 2.0) (* 2.0 x)) (- (/ 1.0 2.0))))))
double code(double F, double B, double x) {
return -(x * (1.0 / tan(B))) + ((F / sin(B)) * pow((((F * F) + 2.0) + (2.0 * x)), -(1.0 / 2.0)));
}
real(8) function code(f, b, x)
real(8), intent (in) :: f
real(8), intent (in) :: b
real(8), intent (in) :: x
code = -(x * (1.0d0 / tan(b))) + ((f / sin(b)) * ((((f * f) + 2.0d0) + (2.0d0 * x)) ** -(1.0d0 / 2.0d0)))
end function
public static double code(double F, double B, double x) {
return -(x * (1.0 / Math.tan(B))) + ((F / Math.sin(B)) * Math.pow((((F * F) + 2.0) + (2.0 * x)), -(1.0 / 2.0)));
}
def code(F, B, x): return -(x * (1.0 / math.tan(B))) + ((F / math.sin(B)) * math.pow((((F * F) + 2.0) + (2.0 * x)), -(1.0 / 2.0)))
function code(F, B, x) return Float64(Float64(-Float64(x * Float64(1.0 / tan(B)))) + Float64(Float64(F / sin(B)) * (Float64(Float64(Float64(F * F) + 2.0) + Float64(2.0 * x)) ^ Float64(-Float64(1.0 / 2.0))))) end
function tmp = code(F, B, x) tmp = -(x * (1.0 / tan(B))) + ((F / sin(B)) * ((((F * F) + 2.0) + (2.0 * x)) ^ -(1.0 / 2.0))); end
code[F_, B_, x_] := N[((-N[(x * N[(1.0 / N[Tan[B], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]) + N[(N[(F / N[Sin[B], $MachinePrecision]), $MachinePrecision] * N[Power[N[(N[(N[(F * F), $MachinePrecision] + 2.0), $MachinePrecision] + N[(2.0 * x), $MachinePrecision]), $MachinePrecision], (-N[(1.0 / 2.0), $MachinePrecision])], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(-x \cdot \frac{1}{\tan B}\right) + \frac{F}{\sin B} \cdot {\left(\left(F \cdot F + 2\right) + 2 \cdot x\right)}^{\left(-\frac{1}{2}\right)}
\end{array}
(FPCore (F B x)
:precision binary64
(if (<= F -1.85e+124)
(fma (/ (/ -1.0 F) (sin B)) F (/ (- x) (tan B)))
(if (<= F 1e+134)
(- (/ (/ F (sqrt (fma 2.0 x (fma F F 2.0)))) (sin B)) (/ x (tan B)))
(+ (* x (/ -1.0 (tan B))) (/ 1.0 (sin B))))))
double code(double F, double B, double x) {
double tmp;
if (F <= -1.85e+124) {
tmp = fma(((-1.0 / F) / sin(B)), F, (-x / tan(B)));
} else if (F <= 1e+134) {
tmp = ((F / sqrt(fma(2.0, x, fma(F, F, 2.0)))) / sin(B)) - (x / tan(B));
} else {
tmp = (x * (-1.0 / tan(B))) + (1.0 / sin(B));
}
return tmp;
}
function code(F, B, x) tmp = 0.0 if (F <= -1.85e+124) tmp = fma(Float64(Float64(-1.0 / F) / sin(B)), F, Float64(Float64(-x) / tan(B))); elseif (F <= 1e+134) tmp = Float64(Float64(Float64(F / sqrt(fma(2.0, x, fma(F, F, 2.0)))) / sin(B)) - Float64(x / tan(B))); else tmp = Float64(Float64(x * Float64(-1.0 / tan(B))) + Float64(1.0 / sin(B))); end return tmp end
code[F_, B_, x_] := If[LessEqual[F, -1.85e+124], N[(N[(N[(-1.0 / F), $MachinePrecision] / N[Sin[B], $MachinePrecision]), $MachinePrecision] * F + N[((-x) / N[Tan[B], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[F, 1e+134], N[(N[(N[(F / N[Sqrt[N[(2.0 * x + N[(F * F + 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sin[B], $MachinePrecision]), $MachinePrecision] - N[(x / N[Tan[B], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * N[(-1.0 / N[Tan[B], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(1.0 / N[Sin[B], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;F \leq -1.85 \cdot 10^{+124}:\\
\;\;\;\;\mathsf{fma}\left(\frac{\frac{-1}{F}}{\sin B}, F, \frac{-x}{\tan B}\right)\\
\mathbf{elif}\;F \leq 10^{+134}:\\
\;\;\;\;\frac{\frac{F}{\sqrt{\mathsf{fma}\left(2, x, \mathsf{fma}\left(F, F, 2\right)\right)}}}{\sin B} - \frac{x}{\tan B}\\
\mathbf{else}:\\
\;\;\;\;x \cdot \frac{-1}{\tan B} + \frac{1}{\sin B}\\
\end{array}
\end{array}
if F < -1.85000000000000004e124Initial program 38.8%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
associate-*r*N/A
div-invN/A
lower-fma.f64N/A
Applied rewrites51.4%
Taylor expanded in F around -inf
lower-/.f6499.8
Applied rewrites99.8%
if -1.85000000000000004e124 < F < 9.99999999999999921e133Initial program 98.2%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
associate-*r*N/A
div-invN/A
lower-fma.f64N/A
Applied rewrites99.6%
lift-fma.f64N/A
lift-/.f64N/A
div-invN/A
lift-neg.f64N/A
lift-/.f64N/A
distribute-lft-neg-inN/A
lift-*.f64N/A
unsub-negN/A
lower--.f64N/A
Applied rewrites99.7%
lift-/.f64N/A
lift-*.f64N/A
*-commutativeN/A
associate-/r*N/A
lift-/.f64N/A
lower-/.f6499.7
Applied rewrites99.7%
if 9.99999999999999921e133 < F Initial program 41.3%
Taylor expanded in F around inf
lower-/.f64N/A
lower-sin.f6499.8
Applied rewrites99.8%
Final simplification99.7%
(FPCore (F B x)
:precision binary64
(let* ((t_0 (/ x (tan B))))
(if (<= F -6.5e+15)
(- (/ -1.0 (sin B)) t_0)
(if (<= F 100000000.0)
(- (/ F (* (sin B) (sqrt (fma 2.0 x (fma F F 2.0))))) t_0)
(- (/ 1.0 (sin B)) t_0)))))
double code(double F, double B, double x) {
double t_0 = x / tan(B);
double tmp;
if (F <= -6.5e+15) {
tmp = (-1.0 / sin(B)) - t_0;
} else if (F <= 100000000.0) {
tmp = (F / (sin(B) * sqrt(fma(2.0, x, fma(F, F, 2.0))))) - t_0;
} else {
tmp = (1.0 / sin(B)) - t_0;
}
return tmp;
}
function code(F, B, x) t_0 = Float64(x / tan(B)) tmp = 0.0 if (F <= -6.5e+15) tmp = Float64(Float64(-1.0 / sin(B)) - t_0); elseif (F <= 100000000.0) tmp = Float64(Float64(F / Float64(sin(B) * sqrt(fma(2.0, x, fma(F, F, 2.0))))) - t_0); else tmp = Float64(Float64(1.0 / sin(B)) - t_0); end return tmp end
code[F_, B_, x_] := Block[{t$95$0 = N[(x / N[Tan[B], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[F, -6.5e+15], N[(N[(-1.0 / N[Sin[B], $MachinePrecision]), $MachinePrecision] - t$95$0), $MachinePrecision], If[LessEqual[F, 100000000.0], N[(N[(F / N[(N[Sin[B], $MachinePrecision] * N[Sqrt[N[(2.0 * x + N[(F * F + 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$0), $MachinePrecision], N[(N[(1.0 / N[Sin[B], $MachinePrecision]), $MachinePrecision] - t$95$0), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{x}{\tan B}\\
\mathbf{if}\;F \leq -6.5 \cdot 10^{+15}:\\
\;\;\;\;\frac{-1}{\sin B} - t\_0\\
\mathbf{elif}\;F \leq 100000000:\\
\;\;\;\;\frac{F}{\sin B \cdot \sqrt{\mathsf{fma}\left(2, x, \mathsf{fma}\left(F, F, 2\right)\right)}} - t\_0\\
\mathbf{else}:\\
\;\;\;\;\frac{1}{\sin B} - t\_0\\
\end{array}
\end{array}
if F < -6.5e15Initial program 58.0%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
associate-*r*N/A
div-invN/A
lower-fma.f64N/A
Applied rewrites71.9%
lift-fma.f64N/A
lift-/.f64N/A
div-invN/A
lift-neg.f64N/A
lift-/.f64N/A
distribute-lft-neg-inN/A
lift-*.f64N/A
unsub-negN/A
lower--.f64N/A
Applied rewrites72.0%
Taylor expanded in F around -inf
lower-/.f64N/A
lower-sin.f6499.8
Applied rewrites99.8%
if -6.5e15 < F < 1e8Initial program 99.4%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
associate-*r*N/A
div-invN/A
lower-fma.f64N/A
Applied rewrites99.6%
lift-fma.f64N/A
lift-/.f64N/A
div-invN/A
lift-neg.f64N/A
lift-/.f64N/A
distribute-lft-neg-inN/A
lift-*.f64N/A
unsub-negN/A
lower--.f64N/A
Applied rewrites99.6%
if 1e8 < F Initial program 56.4%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
associate-*r*N/A
div-invN/A
lower-fma.f64N/A
Applied rewrites71.7%
lift-fma.f64N/A
lift-/.f64N/A
div-invN/A
lift-neg.f64N/A
lift-/.f64N/A
distribute-lft-neg-inN/A
lift-*.f64N/A
unsub-negN/A
lower--.f64N/A
Applied rewrites71.8%
Taylor expanded in F around inf
lower-/.f64N/A
lower-sin.f6499.8
Applied rewrites99.8%
herbie shell --seed 2024230
(FPCore (F B x)
:name "VandenBroeck and Keller, Equation (23)"
:precision binary64
(+ (- (* x (/ 1.0 (tan B)))) (* (/ F (sin B)) (pow (+ (+ (* F F) 2.0) (* 2.0 x)) (- (/ 1.0 2.0))))))