
(FPCore (x) :precision binary64 (let* ((t_0 (sin (* x 0.5)))) (/ (* (* (/ 8.0 3.0) t_0) t_0) (sin x))))
double code(double x) {
double t_0 = sin((x * 0.5));
return (((8.0 / 3.0) * t_0) * t_0) / sin(x);
}
real(8) function code(x)
real(8), intent (in) :: x
real(8) :: t_0
t_0 = sin((x * 0.5d0))
code = (((8.0d0 / 3.0d0) * t_0) * t_0) / sin(x)
end function
public static double code(double x) {
double t_0 = Math.sin((x * 0.5));
return (((8.0 / 3.0) * t_0) * t_0) / Math.sin(x);
}
def code(x): t_0 = math.sin((x * 0.5)) return (((8.0 / 3.0) * t_0) * t_0) / math.sin(x)
function code(x) t_0 = sin(Float64(x * 0.5)) return Float64(Float64(Float64(Float64(8.0 / 3.0) * t_0) * t_0) / sin(x)) end
function tmp = code(x) t_0 = sin((x * 0.5)); tmp = (((8.0 / 3.0) * t_0) * t_0) / sin(x); end
code[x_] := Block[{t$95$0 = N[Sin[N[(x * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[(N[(8.0 / 3.0), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision] / N[Sin[x], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(x \cdot 0.5\right)\\
\frac{\left(\frac{8}{3} \cdot t_0\right) \cdot t_0}{\sin x}
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 15 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (x) :precision binary64 (let* ((t_0 (sin (* x 0.5)))) (/ (* (* (/ 8.0 3.0) t_0) t_0) (sin x))))
double code(double x) {
double t_0 = sin((x * 0.5));
return (((8.0 / 3.0) * t_0) * t_0) / sin(x);
}
real(8) function code(x)
real(8), intent (in) :: x
real(8) :: t_0
t_0 = sin((x * 0.5d0))
code = (((8.0d0 / 3.0d0) * t_0) * t_0) / sin(x)
end function
public static double code(double x) {
double t_0 = Math.sin((x * 0.5));
return (((8.0 / 3.0) * t_0) * t_0) / Math.sin(x);
}
def code(x): t_0 = math.sin((x * 0.5)) return (((8.0 / 3.0) * t_0) * t_0) / math.sin(x)
function code(x) t_0 = sin(Float64(x * 0.5)) return Float64(Float64(Float64(Float64(8.0 / 3.0) * t_0) * t_0) / sin(x)) end
function tmp = code(x) t_0 = sin((x * 0.5)); tmp = (((8.0 / 3.0) * t_0) * t_0) / sin(x); end
code[x_] := Block[{t$95$0 = N[Sin[N[(x * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[(N[(8.0 / 3.0), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision] / N[Sin[x], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(x \cdot 0.5\right)\\
\frac{\left(\frac{8}{3} \cdot t_0\right) \cdot t_0}{\sin x}
\end{array}
\end{array}
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(let* ((t_0 (sin (* x_m 0.5))))
(*
x_s
(if (<= x_m 0.0002)
(* (/ t_0 0.375) (+ 0.5 (* (pow x_m 2.0) 0.0625)))
(/ (pow t_0 2.0) (* (sin x_m) 0.375))))))x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double t_0 = sin((x_m * 0.5));
double tmp;
if (x_m <= 0.0002) {
tmp = (t_0 / 0.375) * (0.5 + (pow(x_m, 2.0) * 0.0625));
} else {
tmp = pow(t_0, 2.0) / (sin(x_m) * 0.375);
}
return x_s * tmp;
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: t_0
real(8) :: tmp
t_0 = sin((x_m * 0.5d0))
if (x_m <= 0.0002d0) then
tmp = (t_0 / 0.375d0) * (0.5d0 + ((x_m ** 2.0d0) * 0.0625d0))
else
tmp = (t_0 ** 2.0d0) / (sin(x_m) * 0.375d0)
end if
code = x_s * tmp
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double t_0 = Math.sin((x_m * 0.5));
double tmp;
if (x_m <= 0.0002) {
tmp = (t_0 / 0.375) * (0.5 + (Math.pow(x_m, 2.0) * 0.0625));
} else {
tmp = Math.pow(t_0, 2.0) / (Math.sin(x_m) * 0.375);
}
return x_s * tmp;
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): t_0 = math.sin((x_m * 0.5)) tmp = 0 if x_m <= 0.0002: tmp = (t_0 / 0.375) * (0.5 + (math.pow(x_m, 2.0) * 0.0625)) else: tmp = math.pow(t_0, 2.0) / (math.sin(x_m) * 0.375) return x_s * tmp
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) t_0 = sin(Float64(x_m * 0.5)) tmp = 0.0 if (x_m <= 0.0002) tmp = Float64(Float64(t_0 / 0.375) * Float64(0.5 + Float64((x_m ^ 2.0) * 0.0625))); else tmp = Float64((t_0 ^ 2.0) / Float64(sin(x_m) * 0.375)); end return Float64(x_s * tmp) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp_2 = code(x_s, x_m) t_0 = sin((x_m * 0.5)); tmp = 0.0; if (x_m <= 0.0002) tmp = (t_0 / 0.375) * (0.5 + ((x_m ^ 2.0) * 0.0625)); else tmp = (t_0 ^ 2.0) / (sin(x_m) * 0.375); end tmp_2 = x_s * tmp; end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := Block[{t$95$0 = N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(x$95$s * If[LessEqual[x$95$m, 0.0002], N[(N[(t$95$0 / 0.375), $MachinePrecision] * N[(0.5 + N[(N[Power[x$95$m, 2.0], $MachinePrecision] * 0.0625), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[Power[t$95$0, 2.0], $MachinePrecision] / N[(N[Sin[x$95$m], $MachinePrecision] * 0.375), $MachinePrecision]), $MachinePrecision]]), $MachinePrecision]]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
\begin{array}{l}
t_0 := \sin \left(x_m \cdot 0.5\right)\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 0.0002:\\
\;\;\;\;\frac{t_0}{0.375} \cdot \left(0.5 + {x_m}^{2} \cdot 0.0625\right)\\
\mathbf{else}:\\
\;\;\;\;\frac{{t_0}^{2}}{\sin x_m \cdot 0.375}\\
\end{array}
\end{array}
\end{array}
if x < 2.0000000000000001e-4Initial program 68.3%
associate-/l*99.3%
*-commutative99.3%
*-lft-identity99.3%
metadata-eval99.3%
times-frac99.3%
associate-/l*99.3%
*-commutative99.3%
neg-mul-199.3%
sin-neg99.3%
distribute-lft-neg-out99.3%
times-frac99.3%
*-commutative99.3%
associate-/l/99.3%
associate-/r*99.3%
Simplified99.3%
associate-/r/99.3%
*-commutative99.3%
associate-*l/99.2%
associate-/r/99.2%
associate-*l/68.3%
div-inv68.5%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
Taylor expanded in x around 0 62.5%
*-commutative62.5%
Simplified62.5%
if 2.0000000000000001e-4 < x Initial program 98.9%
*-commutative98.9%
remove-double-neg98.9%
sin-neg98.9%
distribute-lft-neg-out98.9%
distribute-rgt-neg-in98.9%
associate-*l/98.9%
*-commutative98.9%
distribute-rgt-neg-in98.9%
distribute-lft-neg-out98.9%
sin-neg98.9%
remove-double-neg98.9%
associate-*l*98.9%
Simplified98.9%
*-commutative98.9%
associate-*r/99.1%
associate-/r/99.1%
pow299.1%
div-inv99.2%
metadata-eval99.2%
Applied egg-rr99.2%
Final simplification70.8%
x_m = (fabs.f64 x) x_s = (copysign.f64 1 x) (FPCore (x_s x_m) :precision binary64 (let* ((t_0 (sin (* x_m 0.5)))) (* x_s (* (/ 1.0 (/ (sin x_m) t_0)) (/ t_0 0.375)))))
x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double t_0 = sin((x_m * 0.5));
return x_s * ((1.0 / (sin(x_m) / t_0)) * (t_0 / 0.375));
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: t_0
t_0 = sin((x_m * 0.5d0))
code = x_s * ((1.0d0 / (sin(x_m) / t_0)) * (t_0 / 0.375d0))
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double t_0 = Math.sin((x_m * 0.5));
return x_s * ((1.0 / (Math.sin(x_m) / t_0)) * (t_0 / 0.375));
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): t_0 = math.sin((x_m * 0.5)) return x_s * ((1.0 / (math.sin(x_m) / t_0)) * (t_0 / 0.375))
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) t_0 = sin(Float64(x_m * 0.5)) return Float64(x_s * Float64(Float64(1.0 / Float64(sin(x_m) / t_0)) * Float64(t_0 / 0.375))) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp = code(x_s, x_m) t_0 = sin((x_m * 0.5)); tmp = x_s * ((1.0 / (sin(x_m) / t_0)) * (t_0 / 0.375)); end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := Block[{t$95$0 = N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(x$95$s * N[(N[(1.0 / N[(N[Sin[x$95$m], $MachinePrecision] / t$95$0), $MachinePrecision]), $MachinePrecision] * N[(t$95$0 / 0.375), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
\begin{array}{l}
t_0 := \sin \left(x_m \cdot 0.5\right)\\
x_s \cdot \left(\frac{1}{\frac{\sin x_m}{t_0}} \cdot \frac{t_0}{0.375}\right)
\end{array}
\end{array}
Initial program 75.2%
associate-/l*99.2%
*-commutative99.2%
*-lft-identity99.2%
metadata-eval99.2%
times-frac99.2%
associate-/l*99.2%
*-commutative99.2%
neg-mul-199.2%
sin-neg99.2%
distribute-lft-neg-out99.2%
times-frac99.2%
*-commutative99.2%
associate-/l/99.2%
associate-/r*99.2%
Simplified99.2%
associate-/r/99.2%
*-commutative99.2%
associate-*l/99.1%
associate-/r/99.2%
associate-*l/75.3%
div-inv75.4%
times-frac99.4%
metadata-eval99.4%
Applied egg-rr99.4%
clear-num99.4%
inv-pow99.4%
Applied egg-rr99.4%
unpow-199.4%
Applied egg-rr99.4%
Final simplification99.4%
x_m = (fabs.f64 x) x_s = (copysign.f64 1 x) (FPCore (x_s x_m) :precision binary64 (let* ((t_0 (sin (* x_m 0.5)))) (* x_s (* 2.6666666666666665 (* t_0 (/ t_0 (sin x_m)))))))
x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double t_0 = sin((x_m * 0.5));
return x_s * (2.6666666666666665 * (t_0 * (t_0 / sin(x_m))));
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: t_0
t_0 = sin((x_m * 0.5d0))
code = x_s * (2.6666666666666665d0 * (t_0 * (t_0 / sin(x_m))))
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double t_0 = Math.sin((x_m * 0.5));
return x_s * (2.6666666666666665 * (t_0 * (t_0 / Math.sin(x_m))));
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): t_0 = math.sin((x_m * 0.5)) return x_s * (2.6666666666666665 * (t_0 * (t_0 / math.sin(x_m))))
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) t_0 = sin(Float64(x_m * 0.5)) return Float64(x_s * Float64(2.6666666666666665 * Float64(t_0 * Float64(t_0 / sin(x_m))))) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp = code(x_s, x_m) t_0 = sin((x_m * 0.5)); tmp = x_s * (2.6666666666666665 * (t_0 * (t_0 / sin(x_m)))); end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := Block[{t$95$0 = N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(x$95$s * N[(2.6666666666666665 * N[(t$95$0 * N[(t$95$0 / N[Sin[x$95$m], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
\begin{array}{l}
t_0 := \sin \left(x_m \cdot 0.5\right)\\
x_s \cdot \left(2.6666666666666665 \cdot \left(t_0 \cdot \frac{t_0}{\sin x_m}\right)\right)
\end{array}
\end{array}
Initial program 75.2%
*-commutative75.2%
remove-double-neg75.2%
sin-neg75.2%
distribute-lft-neg-out75.2%
distribute-rgt-neg-in75.2%
associate-*l/99.1%
*-commutative99.1%
distribute-rgt-neg-in99.1%
distribute-lft-neg-out99.1%
sin-neg99.1%
remove-double-neg99.1%
associate-*l*99.1%
Simplified99.1%
Final simplification99.1%
x_m = (fabs.f64 x) x_s = (copysign.f64 1 x) (FPCore (x_s x_m) :precision binary64 (let* ((t_0 (sin (* x_m 0.5)))) (* x_s (* t_0 (/ t_0 (/ (sin x_m) 2.6666666666666665))))))
x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double t_0 = sin((x_m * 0.5));
return x_s * (t_0 * (t_0 / (sin(x_m) / 2.6666666666666665)));
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: t_0
t_0 = sin((x_m * 0.5d0))
code = x_s * (t_0 * (t_0 / (sin(x_m) / 2.6666666666666665d0)))
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double t_0 = Math.sin((x_m * 0.5));
return x_s * (t_0 * (t_0 / (Math.sin(x_m) / 2.6666666666666665)));
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): t_0 = math.sin((x_m * 0.5)) return x_s * (t_0 * (t_0 / (math.sin(x_m) / 2.6666666666666665)))
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) t_0 = sin(Float64(x_m * 0.5)) return Float64(x_s * Float64(t_0 * Float64(t_0 / Float64(sin(x_m) / 2.6666666666666665)))) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp = code(x_s, x_m) t_0 = sin((x_m * 0.5)); tmp = x_s * (t_0 * (t_0 / (sin(x_m) / 2.6666666666666665))); end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := Block[{t$95$0 = N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(x$95$s * N[(t$95$0 * N[(t$95$0 / N[(N[Sin[x$95$m], $MachinePrecision] / 2.6666666666666665), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
\begin{array}{l}
t_0 := \sin \left(x_m \cdot 0.5\right)\\
x_s \cdot \left(t_0 \cdot \frac{t_0}{\frac{\sin x_m}{2.6666666666666665}}\right)
\end{array}
\end{array}
Initial program 75.2%
*-commutative75.2%
remove-double-neg75.2%
sin-neg75.2%
distribute-lft-neg-out75.2%
distribute-rgt-neg-in75.2%
associate-*r/99.2%
*-commutative99.2%
distribute-lft-neg-in99.2%
distribute-lft-neg-out99.2%
sin-neg99.2%
remove-double-neg99.2%
Simplified99.2%
Final simplification99.2%
x_m = (fabs.f64 x) x_s = (copysign.f64 1 x) (FPCore (x_s x_m) :precision binary64 (let* ((t_0 (sin (* x_m 0.5)))) (* x_s (* (/ t_0 0.375) (/ t_0 (sin x_m))))))
x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double t_0 = sin((x_m * 0.5));
return x_s * ((t_0 / 0.375) * (t_0 / sin(x_m)));
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: t_0
t_0 = sin((x_m * 0.5d0))
code = x_s * ((t_0 / 0.375d0) * (t_0 / sin(x_m)))
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double t_0 = Math.sin((x_m * 0.5));
return x_s * ((t_0 / 0.375) * (t_0 / Math.sin(x_m)));
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): t_0 = math.sin((x_m * 0.5)) return x_s * ((t_0 / 0.375) * (t_0 / math.sin(x_m)))
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) t_0 = sin(Float64(x_m * 0.5)) return Float64(x_s * Float64(Float64(t_0 / 0.375) * Float64(t_0 / sin(x_m)))) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp = code(x_s, x_m) t_0 = sin((x_m * 0.5)); tmp = x_s * ((t_0 / 0.375) * (t_0 / sin(x_m))); end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := Block[{t$95$0 = N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(x$95$s * N[(N[(t$95$0 / 0.375), $MachinePrecision] * N[(t$95$0 / N[Sin[x$95$m], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
\begin{array}{l}
t_0 := \sin \left(x_m \cdot 0.5\right)\\
x_s \cdot \left(\frac{t_0}{0.375} \cdot \frac{t_0}{\sin x_m}\right)
\end{array}
\end{array}
Initial program 75.2%
associate-/l*99.2%
*-commutative99.2%
*-lft-identity99.2%
metadata-eval99.2%
times-frac99.2%
associate-/l*99.2%
*-commutative99.2%
neg-mul-199.2%
sin-neg99.2%
distribute-lft-neg-out99.2%
times-frac99.2%
*-commutative99.2%
associate-/l/99.2%
associate-/r*99.2%
Simplified99.2%
associate-/r/99.2%
*-commutative99.2%
associate-*l/99.1%
associate-/r/99.2%
associate-*l/75.3%
div-inv75.4%
times-frac99.4%
metadata-eval99.4%
Applied egg-rr99.4%
Final simplification99.4%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(let* ((t_0 (sin (* x_m 0.5))))
(*
x_s
(if (<= x_m 5e-7)
(* (/ t_0 0.375) (+ 0.5 (* (pow x_m 2.0) 0.0625)))
(* 2.6666666666666665 (/ (pow t_0 2.0) (sin x_m)))))))x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double t_0 = sin((x_m * 0.5));
double tmp;
if (x_m <= 5e-7) {
tmp = (t_0 / 0.375) * (0.5 + (pow(x_m, 2.0) * 0.0625));
} else {
tmp = 2.6666666666666665 * (pow(t_0, 2.0) / sin(x_m));
}
return x_s * tmp;
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: t_0
real(8) :: tmp
t_0 = sin((x_m * 0.5d0))
if (x_m <= 5d-7) then
tmp = (t_0 / 0.375d0) * (0.5d0 + ((x_m ** 2.0d0) * 0.0625d0))
else
tmp = 2.6666666666666665d0 * ((t_0 ** 2.0d0) / sin(x_m))
end if
code = x_s * tmp
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double t_0 = Math.sin((x_m * 0.5));
double tmp;
if (x_m <= 5e-7) {
tmp = (t_0 / 0.375) * (0.5 + (Math.pow(x_m, 2.0) * 0.0625));
} else {
tmp = 2.6666666666666665 * (Math.pow(t_0, 2.0) / Math.sin(x_m));
}
return x_s * tmp;
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): t_0 = math.sin((x_m * 0.5)) tmp = 0 if x_m <= 5e-7: tmp = (t_0 / 0.375) * (0.5 + (math.pow(x_m, 2.0) * 0.0625)) else: tmp = 2.6666666666666665 * (math.pow(t_0, 2.0) / math.sin(x_m)) return x_s * tmp
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) t_0 = sin(Float64(x_m * 0.5)) tmp = 0.0 if (x_m <= 5e-7) tmp = Float64(Float64(t_0 / 0.375) * Float64(0.5 + Float64((x_m ^ 2.0) * 0.0625))); else tmp = Float64(2.6666666666666665 * Float64((t_0 ^ 2.0) / sin(x_m))); end return Float64(x_s * tmp) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp_2 = code(x_s, x_m) t_0 = sin((x_m * 0.5)); tmp = 0.0; if (x_m <= 5e-7) tmp = (t_0 / 0.375) * (0.5 + ((x_m ^ 2.0) * 0.0625)); else tmp = 2.6666666666666665 * ((t_0 ^ 2.0) / sin(x_m)); end tmp_2 = x_s * tmp; end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := Block[{t$95$0 = N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(x$95$s * If[LessEqual[x$95$m, 5e-7], N[(N[(t$95$0 / 0.375), $MachinePrecision] * N[(0.5 + N[(N[Power[x$95$m, 2.0], $MachinePrecision] * 0.0625), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(2.6666666666666665 * N[(N[Power[t$95$0, 2.0], $MachinePrecision] / N[Sin[x$95$m], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]), $MachinePrecision]]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
\begin{array}{l}
t_0 := \sin \left(x_m \cdot 0.5\right)\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 5 \cdot 10^{-7}:\\
\;\;\;\;\frac{t_0}{0.375} \cdot \left(0.5 + {x_m}^{2} \cdot 0.0625\right)\\
\mathbf{else}:\\
\;\;\;\;2.6666666666666665 \cdot \frac{{t_0}^{2}}{\sin x_m}\\
\end{array}
\end{array}
\end{array}
if x < 4.99999999999999977e-7Initial program 68.3%
associate-/l*99.3%
*-commutative99.3%
*-lft-identity99.3%
metadata-eval99.3%
times-frac99.3%
associate-/l*99.3%
*-commutative99.3%
neg-mul-199.3%
sin-neg99.3%
distribute-lft-neg-out99.3%
times-frac99.3%
*-commutative99.3%
associate-/l/99.3%
associate-/r*99.3%
Simplified99.3%
associate-/r/99.3%
*-commutative99.3%
associate-*l/99.2%
associate-/r/99.2%
associate-*l/68.3%
div-inv68.5%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
Taylor expanded in x around 0 62.5%
*-commutative62.5%
Simplified62.5%
if 4.99999999999999977e-7 < x Initial program 98.9%
associate-/l*99.0%
*-commutative99.0%
*-lft-identity99.0%
metadata-eval99.0%
times-frac98.9%
associate-/l*98.9%
*-commutative98.9%
neg-mul-198.9%
sin-neg98.9%
distribute-lft-neg-out98.9%
times-frac99.0%
*-commutative99.0%
associate-/l/99.0%
associate-/r*99.0%
Simplified99.0%
div-inv98.9%
clear-num98.9%
associate-*r*98.9%
*-commutative98.9%
associate-*r/99.1%
pow299.1%
Applied egg-rr99.1%
Final simplification70.8%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(let* ((t_0 (sin (* x_m 0.5))))
(*
x_s
(if (<= x_m 5e-9)
(* 0.5 (/ t_0 0.375))
(* (pow t_0 2.0) (/ 2.6666666666666665 (sin x_m)))))))x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double t_0 = sin((x_m * 0.5));
double tmp;
if (x_m <= 5e-9) {
tmp = 0.5 * (t_0 / 0.375);
} else {
tmp = pow(t_0, 2.0) * (2.6666666666666665 / sin(x_m));
}
return x_s * tmp;
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: t_0
real(8) :: tmp
t_0 = sin((x_m * 0.5d0))
if (x_m <= 5d-9) then
tmp = 0.5d0 * (t_0 / 0.375d0)
else
tmp = (t_0 ** 2.0d0) * (2.6666666666666665d0 / sin(x_m))
end if
code = x_s * tmp
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double t_0 = Math.sin((x_m * 0.5));
double tmp;
if (x_m <= 5e-9) {
tmp = 0.5 * (t_0 / 0.375);
} else {
tmp = Math.pow(t_0, 2.0) * (2.6666666666666665 / Math.sin(x_m));
}
return x_s * tmp;
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): t_0 = math.sin((x_m * 0.5)) tmp = 0 if x_m <= 5e-9: tmp = 0.5 * (t_0 / 0.375) else: tmp = math.pow(t_0, 2.0) * (2.6666666666666665 / math.sin(x_m)) return x_s * tmp
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) t_0 = sin(Float64(x_m * 0.5)) tmp = 0.0 if (x_m <= 5e-9) tmp = Float64(0.5 * Float64(t_0 / 0.375)); else tmp = Float64((t_0 ^ 2.0) * Float64(2.6666666666666665 / sin(x_m))); end return Float64(x_s * tmp) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp_2 = code(x_s, x_m) t_0 = sin((x_m * 0.5)); tmp = 0.0; if (x_m <= 5e-9) tmp = 0.5 * (t_0 / 0.375); else tmp = (t_0 ^ 2.0) * (2.6666666666666665 / sin(x_m)); end tmp_2 = x_s * tmp; end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := Block[{t$95$0 = N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(x$95$s * If[LessEqual[x$95$m, 5e-9], N[(0.5 * N[(t$95$0 / 0.375), $MachinePrecision]), $MachinePrecision], N[(N[Power[t$95$0, 2.0], $MachinePrecision] * N[(2.6666666666666665 / N[Sin[x$95$m], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]), $MachinePrecision]]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
\begin{array}{l}
t_0 := \sin \left(x_m \cdot 0.5\right)\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 5 \cdot 10^{-9}:\\
\;\;\;\;0.5 \cdot \frac{t_0}{0.375}\\
\mathbf{else}:\\
\;\;\;\;{t_0}^{2} \cdot \frac{2.6666666666666665}{\sin x_m}\\
\end{array}
\end{array}
\end{array}
if x < 5.0000000000000001e-9Initial program 68.2%
associate-/l*99.3%
*-commutative99.3%
*-lft-identity99.3%
metadata-eval99.3%
times-frac99.3%
associate-/l*99.3%
*-commutative99.3%
neg-mul-199.3%
sin-neg99.3%
distribute-lft-neg-out99.3%
times-frac99.3%
*-commutative99.3%
associate-/l/99.3%
associate-/r*99.3%
Simplified99.3%
associate-/r/99.3%
*-commutative99.3%
associate-*l/99.2%
associate-/r/99.2%
associate-*l/68.2%
div-inv68.3%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
Taylor expanded in x around 0 65.3%
if 5.0000000000000001e-9 < x Initial program 98.9%
associate-/l*99.0%
*-commutative99.0%
*-lft-identity99.0%
metadata-eval99.0%
times-frac98.9%
associate-/l*98.9%
*-commutative98.9%
neg-mul-198.9%
sin-neg98.9%
distribute-lft-neg-out98.9%
times-frac99.0%
*-commutative99.0%
associate-/l/99.0%
associate-/r*99.0%
Simplified99.0%
associate-/r/99.0%
*-commutative99.0%
associate-*l/98.8%
associate-/r/99.0%
associate-*l/99.1%
div-inv99.0%
pow299.0%
clear-num99.1%
Applied egg-rr99.1%
Final simplification73.1%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(let* ((t_0 (sin (* x_m 0.5))))
(*
x_s
(if (<= x_m 5e-9)
(* 0.5 (/ t_0 0.375))
(/ (/ (pow t_0 2.0) (sin x_m)) 0.375)))))x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double t_0 = sin((x_m * 0.5));
double tmp;
if (x_m <= 5e-9) {
tmp = 0.5 * (t_0 / 0.375);
} else {
tmp = (pow(t_0, 2.0) / sin(x_m)) / 0.375;
}
return x_s * tmp;
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: t_0
real(8) :: tmp
t_0 = sin((x_m * 0.5d0))
if (x_m <= 5d-9) then
tmp = 0.5d0 * (t_0 / 0.375d0)
else
tmp = ((t_0 ** 2.0d0) / sin(x_m)) / 0.375d0
end if
code = x_s * tmp
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double t_0 = Math.sin((x_m * 0.5));
double tmp;
if (x_m <= 5e-9) {
tmp = 0.5 * (t_0 / 0.375);
} else {
tmp = (Math.pow(t_0, 2.0) / Math.sin(x_m)) / 0.375;
}
return x_s * tmp;
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): t_0 = math.sin((x_m * 0.5)) tmp = 0 if x_m <= 5e-9: tmp = 0.5 * (t_0 / 0.375) else: tmp = (math.pow(t_0, 2.0) / math.sin(x_m)) / 0.375 return x_s * tmp
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) t_0 = sin(Float64(x_m * 0.5)) tmp = 0.0 if (x_m <= 5e-9) tmp = Float64(0.5 * Float64(t_0 / 0.375)); else tmp = Float64(Float64((t_0 ^ 2.0) / sin(x_m)) / 0.375); end return Float64(x_s * tmp) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp_2 = code(x_s, x_m) t_0 = sin((x_m * 0.5)); tmp = 0.0; if (x_m <= 5e-9) tmp = 0.5 * (t_0 / 0.375); else tmp = ((t_0 ^ 2.0) / sin(x_m)) / 0.375; end tmp_2 = x_s * tmp; end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := Block[{t$95$0 = N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(x$95$s * If[LessEqual[x$95$m, 5e-9], N[(0.5 * N[(t$95$0 / 0.375), $MachinePrecision]), $MachinePrecision], N[(N[(N[Power[t$95$0, 2.0], $MachinePrecision] / N[Sin[x$95$m], $MachinePrecision]), $MachinePrecision] / 0.375), $MachinePrecision]]), $MachinePrecision]]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
\begin{array}{l}
t_0 := \sin \left(x_m \cdot 0.5\right)\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 5 \cdot 10^{-9}:\\
\;\;\;\;0.5 \cdot \frac{t_0}{0.375}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{{t_0}^{2}}{\sin x_m}}{0.375}\\
\end{array}
\end{array}
\end{array}
if x < 5.0000000000000001e-9Initial program 68.2%
associate-/l*99.3%
*-commutative99.3%
*-lft-identity99.3%
metadata-eval99.3%
times-frac99.3%
associate-/l*99.3%
*-commutative99.3%
neg-mul-199.3%
sin-neg99.3%
distribute-lft-neg-out99.3%
times-frac99.3%
*-commutative99.3%
associate-/l/99.3%
associate-/r*99.3%
Simplified99.3%
associate-/r/99.3%
*-commutative99.3%
associate-*l/99.2%
associate-/r/99.2%
associate-*l/68.2%
div-inv68.3%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
Taylor expanded in x around 0 65.3%
if 5.0000000000000001e-9 < x Initial program 98.9%
*-commutative98.9%
remove-double-neg98.9%
sin-neg98.9%
distribute-lft-neg-out98.9%
distribute-rgt-neg-in98.9%
associate-*l/98.9%
*-commutative98.9%
distribute-rgt-neg-in98.9%
distribute-lft-neg-out98.9%
sin-neg98.9%
remove-double-neg98.9%
associate-*l*98.9%
Simplified98.9%
*-commutative98.9%
associate-*r/99.1%
associate-/r/99.1%
div-inv99.2%
associate-/r*99.2%
pow299.2%
metadata-eval99.2%
Applied egg-rr99.2%
Final simplification73.1%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(*
x_s
(if (<= x_m 0.0036)
(* (/ (sin (* x_m 0.5)) 0.375) (+ 0.5 (* (pow x_m 2.0) 0.0625)))
(/ (fma (cos x_m) -1.3333333333333333 1.3333333333333333) (sin x_m)))))x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double tmp;
if (x_m <= 0.0036) {
tmp = (sin((x_m * 0.5)) / 0.375) * (0.5 + (pow(x_m, 2.0) * 0.0625));
} else {
tmp = fma(cos(x_m), -1.3333333333333333, 1.3333333333333333) / sin(x_m);
}
return x_s * tmp;
}
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) tmp = 0.0 if (x_m <= 0.0036) tmp = Float64(Float64(sin(Float64(x_m * 0.5)) / 0.375) * Float64(0.5 + Float64((x_m ^ 2.0) * 0.0625))); else tmp = Float64(fma(cos(x_m), -1.3333333333333333, 1.3333333333333333) / sin(x_m)); end return Float64(x_s * tmp) end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := N[(x$95$s * If[LessEqual[x$95$m, 0.0036], N[(N[(N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision] / 0.375), $MachinePrecision] * N[(0.5 + N[(N[Power[x$95$m, 2.0], $MachinePrecision] * 0.0625), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[Cos[x$95$m], $MachinePrecision] * -1.3333333333333333 + 1.3333333333333333), $MachinePrecision] / N[Sin[x$95$m], $MachinePrecision]), $MachinePrecision]]), $MachinePrecision]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 0.0036:\\
\;\;\;\;\frac{\sin \left(x_m \cdot 0.5\right)}{0.375} \cdot \left(0.5 + {x_m}^{2} \cdot 0.0625\right)\\
\mathbf{else}:\\
\;\;\;\;\frac{\mathsf{fma}\left(\cos x_m, -1.3333333333333333, 1.3333333333333333\right)}{\sin x_m}\\
\end{array}
\end{array}
if x < 0.0035999999999999999Initial program 68.3%
associate-/l*99.3%
*-commutative99.3%
*-lft-identity99.3%
metadata-eval99.3%
times-frac99.3%
associate-/l*99.3%
*-commutative99.3%
neg-mul-199.3%
sin-neg99.3%
distribute-lft-neg-out99.3%
times-frac99.3%
*-commutative99.3%
associate-/l/99.3%
associate-/r*99.3%
Simplified99.3%
associate-/r/99.3%
*-commutative99.3%
associate-*l/99.2%
associate-/r/99.2%
associate-*l/68.3%
div-inv68.5%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
Taylor expanded in x around 0 62.5%
*-commutative62.5%
Simplified62.5%
if 0.0035999999999999999 < x Initial program 98.9%
associate-/l*99.0%
*-commutative99.0%
*-lft-identity99.0%
metadata-eval99.0%
times-frac98.9%
associate-/l*98.9%
*-commutative98.9%
neg-mul-198.9%
sin-neg98.9%
distribute-lft-neg-out98.9%
times-frac99.0%
*-commutative99.0%
associate-/l/99.0%
associate-/r*99.0%
Simplified99.0%
associate-/l*98.9%
metadata-eval98.9%
clear-num98.9%
associate-/r/98.9%
metadata-eval98.9%
associate-*l*98.9%
pow298.9%
Applied egg-rr98.9%
unpow298.9%
sin-mult98.4%
Applied egg-rr98.4%
div-sub98.4%
+-inverses98.4%
cos-098.4%
metadata-eval98.4%
distribute-lft-out98.4%
metadata-eval98.4%
*-rgt-identity98.4%
Simplified98.4%
Taylor expanded in x around inf 98.6%
associate-*r/98.6%
cancel-sign-sub-inv98.6%
metadata-eval98.6%
*-commutative98.6%
+-commutative98.6%
distribute-rgt-in98.3%
metadata-eval98.3%
associate-*l*98.3%
metadata-eval98.3%
metadata-eval98.3%
fma-def98.7%
metadata-eval98.7%
Simplified98.7%
Final simplification70.7%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(*
x_s
(if (<= x_m 0.0036)
(* (/ (sin (* x_m 0.5)) 0.375) (+ 0.5 (* (pow x_m 2.0) 0.0625)))
(/ 2.6666666666666665 (/ (sin x_m) (+ 0.5 (* (cos x_m) -0.5)))))))x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double tmp;
if (x_m <= 0.0036) {
tmp = (sin((x_m * 0.5)) / 0.375) * (0.5 + (pow(x_m, 2.0) * 0.0625));
} else {
tmp = 2.6666666666666665 / (sin(x_m) / (0.5 + (cos(x_m) * -0.5)));
}
return x_s * tmp;
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: tmp
if (x_m <= 0.0036d0) then
tmp = (sin((x_m * 0.5d0)) / 0.375d0) * (0.5d0 + ((x_m ** 2.0d0) * 0.0625d0))
else
tmp = 2.6666666666666665d0 / (sin(x_m) / (0.5d0 + (cos(x_m) * (-0.5d0))))
end if
code = x_s * tmp
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double tmp;
if (x_m <= 0.0036) {
tmp = (Math.sin((x_m * 0.5)) / 0.375) * (0.5 + (Math.pow(x_m, 2.0) * 0.0625));
} else {
tmp = 2.6666666666666665 / (Math.sin(x_m) / (0.5 + (Math.cos(x_m) * -0.5)));
}
return x_s * tmp;
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): tmp = 0 if x_m <= 0.0036: tmp = (math.sin((x_m * 0.5)) / 0.375) * (0.5 + (math.pow(x_m, 2.0) * 0.0625)) else: tmp = 2.6666666666666665 / (math.sin(x_m) / (0.5 + (math.cos(x_m) * -0.5))) return x_s * tmp
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) tmp = 0.0 if (x_m <= 0.0036) tmp = Float64(Float64(sin(Float64(x_m * 0.5)) / 0.375) * Float64(0.5 + Float64((x_m ^ 2.0) * 0.0625))); else tmp = Float64(2.6666666666666665 / Float64(sin(x_m) / Float64(0.5 + Float64(cos(x_m) * -0.5)))); end return Float64(x_s * tmp) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp_2 = code(x_s, x_m) tmp = 0.0; if (x_m <= 0.0036) tmp = (sin((x_m * 0.5)) / 0.375) * (0.5 + ((x_m ^ 2.0) * 0.0625)); else tmp = 2.6666666666666665 / (sin(x_m) / (0.5 + (cos(x_m) * -0.5))); end tmp_2 = x_s * tmp; end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := N[(x$95$s * If[LessEqual[x$95$m, 0.0036], N[(N[(N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision] / 0.375), $MachinePrecision] * N[(0.5 + N[(N[Power[x$95$m, 2.0], $MachinePrecision] * 0.0625), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(2.6666666666666665 / N[(N[Sin[x$95$m], $MachinePrecision] / N[(0.5 + N[(N[Cos[x$95$m], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]), $MachinePrecision]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 0.0036:\\
\;\;\;\;\frac{\sin \left(x_m \cdot 0.5\right)}{0.375} \cdot \left(0.5 + {x_m}^{2} \cdot 0.0625\right)\\
\mathbf{else}:\\
\;\;\;\;\frac{2.6666666666666665}{\frac{\sin x_m}{0.5 + \cos x_m \cdot -0.5}}\\
\end{array}
\end{array}
if x < 0.0035999999999999999Initial program 68.3%
associate-/l*99.3%
*-commutative99.3%
*-lft-identity99.3%
metadata-eval99.3%
times-frac99.3%
associate-/l*99.3%
*-commutative99.3%
neg-mul-199.3%
sin-neg99.3%
distribute-lft-neg-out99.3%
times-frac99.3%
*-commutative99.3%
associate-/l/99.3%
associate-/r*99.3%
Simplified99.3%
associate-/r/99.3%
*-commutative99.3%
associate-*l/99.2%
associate-/r/99.2%
associate-*l/68.3%
div-inv68.5%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
Taylor expanded in x around 0 62.5%
*-commutative62.5%
Simplified62.5%
if 0.0035999999999999999 < x Initial program 98.9%
associate-/l*99.0%
*-commutative99.0%
*-lft-identity99.0%
metadata-eval99.0%
times-frac98.9%
associate-/l*98.9%
*-commutative98.9%
neg-mul-198.9%
sin-neg98.9%
distribute-lft-neg-out98.9%
times-frac99.0%
*-commutative99.0%
associate-/l/99.0%
associate-/r*99.0%
Simplified99.0%
associate-/l*98.9%
metadata-eval98.9%
clear-num98.9%
associate-/r/98.9%
metadata-eval98.9%
associate-*l*98.9%
pow298.9%
Applied egg-rr98.9%
unpow298.9%
sin-mult98.4%
Applied egg-rr98.4%
div-sub98.4%
+-inverses98.4%
cos-098.4%
metadata-eval98.4%
distribute-lft-out98.4%
metadata-eval98.4%
*-rgt-identity98.4%
Simplified98.4%
associate-*l/98.6%
*-un-lft-identity98.6%
associate-/l*98.8%
sub-neg98.8%
div-inv98.8%
metadata-eval98.8%
distribute-rgt-neg-in98.8%
metadata-eval98.8%
Applied egg-rr98.8%
Final simplification70.7%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(*
x_s
(if (<= x_m 0.000115)
(* 0.5 (/ (sin (* x_m 0.5)) 0.375))
(* 2.6666666666666665 (/ (- 0.5 (* 0.5 (cos x_m))) (sin x_m))))))x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double tmp;
if (x_m <= 0.000115) {
tmp = 0.5 * (sin((x_m * 0.5)) / 0.375);
} else {
tmp = 2.6666666666666665 * ((0.5 - (0.5 * cos(x_m))) / sin(x_m));
}
return x_s * tmp;
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: tmp
if (x_m <= 0.000115d0) then
tmp = 0.5d0 * (sin((x_m * 0.5d0)) / 0.375d0)
else
tmp = 2.6666666666666665d0 * ((0.5d0 - (0.5d0 * cos(x_m))) / sin(x_m))
end if
code = x_s * tmp
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double tmp;
if (x_m <= 0.000115) {
tmp = 0.5 * (Math.sin((x_m * 0.5)) / 0.375);
} else {
tmp = 2.6666666666666665 * ((0.5 - (0.5 * Math.cos(x_m))) / Math.sin(x_m));
}
return x_s * tmp;
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): tmp = 0 if x_m <= 0.000115: tmp = 0.5 * (math.sin((x_m * 0.5)) / 0.375) else: tmp = 2.6666666666666665 * ((0.5 - (0.5 * math.cos(x_m))) / math.sin(x_m)) return x_s * tmp
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) tmp = 0.0 if (x_m <= 0.000115) tmp = Float64(0.5 * Float64(sin(Float64(x_m * 0.5)) / 0.375)); else tmp = Float64(2.6666666666666665 * Float64(Float64(0.5 - Float64(0.5 * cos(x_m))) / sin(x_m))); end return Float64(x_s * tmp) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp_2 = code(x_s, x_m) tmp = 0.0; if (x_m <= 0.000115) tmp = 0.5 * (sin((x_m * 0.5)) / 0.375); else tmp = 2.6666666666666665 * ((0.5 - (0.5 * cos(x_m))) / sin(x_m)); end tmp_2 = x_s * tmp; end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := N[(x$95$s * If[LessEqual[x$95$m, 0.000115], N[(0.5 * N[(N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision] / 0.375), $MachinePrecision]), $MachinePrecision], N[(2.6666666666666665 * N[(N[(0.5 - N[(0.5 * N[Cos[x$95$m], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sin[x$95$m], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]), $MachinePrecision]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 0.000115:\\
\;\;\;\;0.5 \cdot \frac{\sin \left(x_m \cdot 0.5\right)}{0.375}\\
\mathbf{else}:\\
\;\;\;\;2.6666666666666665 \cdot \frac{0.5 - 0.5 \cdot \cos x_m}{\sin x_m}\\
\end{array}
\end{array}
if x < 1.15e-4Initial program 68.3%
associate-/l*99.3%
*-commutative99.3%
*-lft-identity99.3%
metadata-eval99.3%
times-frac99.3%
associate-/l*99.3%
*-commutative99.3%
neg-mul-199.3%
sin-neg99.3%
distribute-lft-neg-out99.3%
times-frac99.3%
*-commutative99.3%
associate-/l/99.3%
associate-/r*99.3%
Simplified99.3%
associate-/r/99.3%
*-commutative99.3%
associate-*l/99.2%
associate-/r/99.2%
associate-*l/68.3%
div-inv68.5%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
Taylor expanded in x around 0 65.4%
if 1.15e-4 < x Initial program 98.9%
associate-/l*99.0%
*-commutative99.0%
*-lft-identity99.0%
metadata-eval99.0%
times-frac98.9%
associate-/l*98.9%
*-commutative98.9%
neg-mul-198.9%
sin-neg98.9%
distribute-lft-neg-out98.9%
times-frac99.0%
*-commutative99.0%
associate-/l/99.0%
associate-/r*99.0%
Simplified99.0%
associate-/l*98.9%
metadata-eval98.9%
clear-num98.9%
associate-/r/98.9%
metadata-eval98.9%
associate-*l*98.9%
pow298.9%
Applied egg-rr98.9%
unpow298.9%
sin-mult98.4%
Applied egg-rr98.4%
div-sub98.4%
+-inverses98.4%
cos-098.4%
metadata-eval98.4%
distribute-lft-out98.4%
metadata-eval98.4%
*-rgt-identity98.4%
Simplified98.4%
Taylor expanded in x around inf 98.6%
Final simplification73.0%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(*
x_s
(if (<= x_m 0.000115)
(* 0.5 (/ (sin (* x_m 0.5)) 0.375))
(/ 2.6666666666666665 (/ (sin x_m) (+ 0.5 (* (cos x_m) -0.5)))))))x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double tmp;
if (x_m <= 0.000115) {
tmp = 0.5 * (sin((x_m * 0.5)) / 0.375);
} else {
tmp = 2.6666666666666665 / (sin(x_m) / (0.5 + (cos(x_m) * -0.5)));
}
return x_s * tmp;
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
real(8) :: tmp
if (x_m <= 0.000115d0) then
tmp = 0.5d0 * (sin((x_m * 0.5d0)) / 0.375d0)
else
tmp = 2.6666666666666665d0 / (sin(x_m) / (0.5d0 + (cos(x_m) * (-0.5d0))))
end if
code = x_s * tmp
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
double tmp;
if (x_m <= 0.000115) {
tmp = 0.5 * (Math.sin((x_m * 0.5)) / 0.375);
} else {
tmp = 2.6666666666666665 / (Math.sin(x_m) / (0.5 + (Math.cos(x_m) * -0.5)));
}
return x_s * tmp;
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): tmp = 0 if x_m <= 0.000115: tmp = 0.5 * (math.sin((x_m * 0.5)) / 0.375) else: tmp = 2.6666666666666665 / (math.sin(x_m) / (0.5 + (math.cos(x_m) * -0.5))) return x_s * tmp
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) tmp = 0.0 if (x_m <= 0.000115) tmp = Float64(0.5 * Float64(sin(Float64(x_m * 0.5)) / 0.375)); else tmp = Float64(2.6666666666666665 / Float64(sin(x_m) / Float64(0.5 + Float64(cos(x_m) * -0.5)))); end return Float64(x_s * tmp) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp_2 = code(x_s, x_m) tmp = 0.0; if (x_m <= 0.000115) tmp = 0.5 * (sin((x_m * 0.5)) / 0.375); else tmp = 2.6666666666666665 / (sin(x_m) / (0.5 + (cos(x_m) * -0.5))); end tmp_2 = x_s * tmp; end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := N[(x$95$s * If[LessEqual[x$95$m, 0.000115], N[(0.5 * N[(N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision] / 0.375), $MachinePrecision]), $MachinePrecision], N[(2.6666666666666665 / N[(N[Sin[x$95$m], $MachinePrecision] / N[(0.5 + N[(N[Cos[x$95$m], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]), $MachinePrecision]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 0.000115:\\
\;\;\;\;0.5 \cdot \frac{\sin \left(x_m \cdot 0.5\right)}{0.375}\\
\mathbf{else}:\\
\;\;\;\;\frac{2.6666666666666665}{\frac{\sin x_m}{0.5 + \cos x_m \cdot -0.5}}\\
\end{array}
\end{array}
if x < 1.15e-4Initial program 68.3%
associate-/l*99.3%
*-commutative99.3%
*-lft-identity99.3%
metadata-eval99.3%
times-frac99.3%
associate-/l*99.3%
*-commutative99.3%
neg-mul-199.3%
sin-neg99.3%
distribute-lft-neg-out99.3%
times-frac99.3%
*-commutative99.3%
associate-/l/99.3%
associate-/r*99.3%
Simplified99.3%
associate-/r/99.3%
*-commutative99.3%
associate-*l/99.2%
associate-/r/99.2%
associate-*l/68.3%
div-inv68.5%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
Taylor expanded in x around 0 65.4%
if 1.15e-4 < x Initial program 98.9%
associate-/l*99.0%
*-commutative99.0%
*-lft-identity99.0%
metadata-eval99.0%
times-frac98.9%
associate-/l*98.9%
*-commutative98.9%
neg-mul-198.9%
sin-neg98.9%
distribute-lft-neg-out98.9%
times-frac99.0%
*-commutative99.0%
associate-/l/99.0%
associate-/r*99.0%
Simplified99.0%
associate-/l*98.9%
metadata-eval98.9%
clear-num98.9%
associate-/r/98.9%
metadata-eval98.9%
associate-*l*98.9%
pow298.9%
Applied egg-rr98.9%
unpow298.9%
sin-mult98.4%
Applied egg-rr98.4%
div-sub98.4%
+-inverses98.4%
cos-098.4%
metadata-eval98.4%
distribute-lft-out98.4%
metadata-eval98.4%
*-rgt-identity98.4%
Simplified98.4%
associate-*l/98.6%
*-un-lft-identity98.6%
associate-/l*98.8%
sub-neg98.8%
div-inv98.8%
metadata-eval98.8%
distribute-rgt-neg-in98.8%
metadata-eval98.8%
Applied egg-rr98.8%
Final simplification73.0%
x_m = (fabs.f64 x) x_s = (copysign.f64 1 x) (FPCore (x_s x_m) :precision binary64 (* x_s (* 0.5 (/ (sin (* x_m 0.5)) 0.375))))
x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
return x_s * (0.5 * (sin((x_m * 0.5)) / 0.375));
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
code = x_s * (0.5d0 * (sin((x_m * 0.5d0)) / 0.375d0))
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
return x_s * (0.5 * (Math.sin((x_m * 0.5)) / 0.375));
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): return x_s * (0.5 * (math.sin((x_m * 0.5)) / 0.375))
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) return Float64(x_s * Float64(0.5 * Float64(sin(Float64(x_m * 0.5)) / 0.375))) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp = code(x_s, x_m) tmp = x_s * (0.5 * (sin((x_m * 0.5)) / 0.375)); end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := N[(x$95$s * N[(0.5 * N[(N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision] / 0.375), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
x_s \cdot \left(0.5 \cdot \frac{\sin \left(x_m \cdot 0.5\right)}{0.375}\right)
\end{array}
Initial program 75.2%
associate-/l*99.2%
*-commutative99.2%
*-lft-identity99.2%
metadata-eval99.2%
times-frac99.2%
associate-/l*99.2%
*-commutative99.2%
neg-mul-199.2%
sin-neg99.2%
distribute-lft-neg-out99.2%
times-frac99.2%
*-commutative99.2%
associate-/l/99.2%
associate-/r*99.2%
Simplified99.2%
associate-/r/99.2%
*-commutative99.2%
associate-*l/99.1%
associate-/r/99.2%
associate-*l/75.3%
div-inv75.4%
times-frac99.4%
metadata-eval99.4%
Applied egg-rr99.4%
Taylor expanded in x around 0 53.7%
Final simplification53.7%
x_m = (fabs.f64 x) x_s = (copysign.f64 1 x) (FPCore (x_s x_m) :precision binary64 (* x_s (* (sin (* x_m 0.5)) 1.3333333333333333)))
x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
return x_s * (sin((x_m * 0.5)) * 1.3333333333333333);
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
code = x_s * (sin((x_m * 0.5d0)) * 1.3333333333333333d0)
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
return x_s * (Math.sin((x_m * 0.5)) * 1.3333333333333333);
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): return x_s * (math.sin((x_m * 0.5)) * 1.3333333333333333)
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) return Float64(x_s * Float64(sin(Float64(x_m * 0.5)) * 1.3333333333333333)) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp = code(x_s, x_m) tmp = x_s * (sin((x_m * 0.5)) * 1.3333333333333333); end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := N[(x$95$s * N[(N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision] * 1.3333333333333333), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
x_s \cdot \left(\sin \left(x_m \cdot 0.5\right) \cdot 1.3333333333333333\right)
\end{array}
Initial program 75.2%
*-commutative75.2%
remove-double-neg75.2%
sin-neg75.2%
distribute-lft-neg-out75.2%
distribute-rgt-neg-in75.2%
associate-*r/99.2%
*-commutative99.2%
distribute-lft-neg-in99.2%
distribute-lft-neg-out99.2%
sin-neg99.2%
remove-double-neg99.2%
Simplified99.2%
Taylor expanded in x around 0 53.4%
Final simplification53.4%
x_m = (fabs.f64 x) x_s = (copysign.f64 1 x) (FPCore (x_s x_m) :precision binary64 (* x_s (* x_m 0.6666666666666666)))
x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
return x_s * (x_m * 0.6666666666666666);
}
x_m = abs(x)
x_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m)
real(8), intent (in) :: x_s
real(8), intent (in) :: x_m
code = x_s * (x_m * 0.6666666666666666d0)
end function
x_m = Math.abs(x);
x_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m) {
return x_s * (x_m * 0.6666666666666666);
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): return x_s * (x_m * 0.6666666666666666)
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) return Float64(x_s * Float64(x_m * 0.6666666666666666)) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp = code(x_s, x_m) tmp = x_s * (x_m * 0.6666666666666666); end
x_m = N[Abs[x], $MachinePrecision]
x_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_] := N[(x$95$s * N[(x$95$m * 0.6666666666666666), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
x_s \cdot \left(x_m \cdot 0.6666666666666666\right)
\end{array}
Initial program 75.2%
associate-/l*99.2%
*-commutative99.2%
*-lft-identity99.2%
metadata-eval99.2%
times-frac99.2%
associate-/l*99.2%
*-commutative99.2%
neg-mul-199.2%
sin-neg99.2%
distribute-lft-neg-out99.2%
times-frac99.2%
*-commutative99.2%
associate-/l/99.2%
associate-/r*99.2%
Simplified99.2%
Taylor expanded in x around 0 49.4%
*-commutative49.4%
Simplified49.4%
Final simplification49.4%
(FPCore (x) :precision binary64 (let* ((t_0 (sin (* x 0.5)))) (/ (/ (* 8.0 t_0) 3.0) (/ (sin x) t_0))))
double code(double x) {
double t_0 = sin((x * 0.5));
return ((8.0 * t_0) / 3.0) / (sin(x) / t_0);
}
real(8) function code(x)
real(8), intent (in) :: x
real(8) :: t_0
t_0 = sin((x * 0.5d0))
code = ((8.0d0 * t_0) / 3.0d0) / (sin(x) / t_0)
end function
public static double code(double x) {
double t_0 = Math.sin((x * 0.5));
return ((8.0 * t_0) / 3.0) / (Math.sin(x) / t_0);
}
def code(x): t_0 = math.sin((x * 0.5)) return ((8.0 * t_0) / 3.0) / (math.sin(x) / t_0)
function code(x) t_0 = sin(Float64(x * 0.5)) return Float64(Float64(Float64(8.0 * t_0) / 3.0) / Float64(sin(x) / t_0)) end
function tmp = code(x) t_0 = sin((x * 0.5)); tmp = ((8.0 * t_0) / 3.0) / (sin(x) / t_0); end
code[x_] := Block[{t$95$0 = N[Sin[N[(x * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[(8.0 * t$95$0), $MachinePrecision] / 3.0), $MachinePrecision] / N[(N[Sin[x], $MachinePrecision] / t$95$0), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(x \cdot 0.5\right)\\
\frac{\frac{8 \cdot t_0}{3}}{\frac{\sin x}{t_0}}
\end{array}
\end{array}
herbie shell --seed 2023322
(FPCore (x)
:name "Graphics.Rasterific.Svg.PathConverter:segmentToBezier from rasterific-svg-0.2.3.1, A"
:precision binary64
:herbie-target
(/ (/ (* 8.0 (sin (* x 0.5))) 3.0) (/ (sin x) (sin (* x 0.5))))
(/ (* (* (/ 8.0 3.0) (sin (* x 0.5))) (sin (* x 0.5))) (sin x)))