
(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 13 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
(*
x_s
(if (<= x_m 5e-12)
(/ (* x_m 0.25) 0.375)
(* (pow (sin (* x_m 0.5)) 2.0) (/ 1.0 (* (sin x_m) 0.375))))))x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double tmp;
if (x_m <= 5e-12) {
tmp = (x_m * 0.25) / 0.375;
} else {
tmp = pow(sin((x_m * 0.5)), 2.0) * (1.0 / (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) :: tmp
if (x_m <= 5d-12) then
tmp = (x_m * 0.25d0) / 0.375d0
else
tmp = (sin((x_m * 0.5d0)) ** 2.0d0) * (1.0d0 / (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 tmp;
if (x_m <= 5e-12) {
tmp = (x_m * 0.25) / 0.375;
} else {
tmp = Math.pow(Math.sin((x_m * 0.5)), 2.0) * (1.0 / (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): tmp = 0 if x_m <= 5e-12: tmp = (x_m * 0.25) / 0.375 else: tmp = math.pow(math.sin((x_m * 0.5)), 2.0) * (1.0 / (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) tmp = 0.0 if (x_m <= 5e-12) tmp = Float64(Float64(x_m * 0.25) / 0.375); else tmp = Float64((sin(Float64(x_m * 0.5)) ^ 2.0) * Float64(1.0 / 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) tmp = 0.0; if (x_m <= 5e-12) tmp = (x_m * 0.25) / 0.375; else tmp = (sin((x_m * 0.5)) ^ 2.0) * (1.0 / (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_] := N[(x$95$s * If[LessEqual[x$95$m, 5e-12], N[(N[(x$95$m * 0.25), $MachinePrecision] / 0.375), $MachinePrecision], N[(N[Power[N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(1.0 / N[(N[Sin[x$95$m], $MachinePrecision] * 0.375), $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 5 \cdot 10^{-12}:\\
\;\;\;\;\frac{x_m \cdot 0.25}{0.375}\\
\mathbf{else}:\\
\;\;\;\;{\sin \left(x_m \cdot 0.5\right)}^{2} \cdot \frac{1}{\sin x_m \cdot 0.375}\\
\end{array}
\end{array}
if x < 4.9999999999999997e-12Initial program 69.4%
*-commutative69.4%
remove-double-neg69.4%
sin-neg69.4%
distribute-lft-neg-out69.4%
distribute-rgt-neg-in69.4%
associate-*l/99.5%
*-commutative99.5%
distribute-rgt-neg-in99.5%
distribute-lft-neg-out99.5%
sin-neg99.5%
remove-double-neg99.5%
associate-*l*99.4%
Simplified99.4%
*-commutative99.4%
associate-*r/69.3%
associate-/r/69.2%
div-inv69.3%
associate-/r*69.4%
pow269.4%
metadata-eval69.4%
Applied egg-rr69.4%
Taylor expanded in x around 0 65.7%
if 4.9999999999999997e-12 < x Initial program 99.2%
*-commutative99.2%
remove-double-neg99.2%
sin-neg99.2%
distribute-lft-neg-out99.2%
distribute-rgt-neg-in99.2%
associate-*l/99.3%
*-commutative99.3%
distribute-rgt-neg-in99.3%
distribute-lft-neg-out99.3%
sin-neg99.3%
remove-double-neg99.3%
associate-*l*99.2%
Simplified99.2%
associate-*r/99.2%
associate-*r/99.1%
associate-/l*99.3%
pow299.3%
Applied egg-rr99.3%
clear-num99.3%
associate-/r/99.1%
clear-num99.2%
unpow299.2%
associate-*l/99.2%
metadata-eval99.2%
div-inv99.2%
associate-*r/99.3%
frac-times99.0%
unpow299.0%
div-inv99.3%
Applied egg-rr99.3%
Final simplification72.7%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(*
x_s
(if (<= x_m 1e-9)
(/ (* x_m 0.25) 0.375)
(* 2.6666666666666665 (/ (pow (sin (* x_m 0.5)) 2.0) (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 <= 1e-9) {
tmp = (x_m * 0.25) / 0.375;
} else {
tmp = 2.6666666666666665 * (pow(sin((x_m * 0.5)), 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) :: tmp
if (x_m <= 1d-9) then
tmp = (x_m * 0.25d0) / 0.375d0
else
tmp = 2.6666666666666665d0 * ((sin((x_m * 0.5d0)) ** 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 tmp;
if (x_m <= 1e-9) {
tmp = (x_m * 0.25) / 0.375;
} else {
tmp = 2.6666666666666665 * (Math.pow(Math.sin((x_m * 0.5)), 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): tmp = 0 if x_m <= 1e-9: tmp = (x_m * 0.25) / 0.375 else: tmp = 2.6666666666666665 * (math.pow(math.sin((x_m * 0.5)), 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) tmp = 0.0 if (x_m <= 1e-9) tmp = Float64(Float64(x_m * 0.25) / 0.375); else tmp = Float64(2.6666666666666665 * Float64((sin(Float64(x_m * 0.5)) ^ 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) tmp = 0.0; if (x_m <= 1e-9) tmp = (x_m * 0.25) / 0.375; else tmp = 2.6666666666666665 * ((sin((x_m * 0.5)) ^ 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_] := N[(x$95$s * If[LessEqual[x$95$m, 1e-9], N[(N[(x$95$m * 0.25), $MachinePrecision] / 0.375), $MachinePrecision], N[(2.6666666666666665 * N[(N[Power[N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision], 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)
\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 10^{-9}:\\
\;\;\;\;\frac{x_m \cdot 0.25}{0.375}\\
\mathbf{else}:\\
\;\;\;\;2.6666666666666665 \cdot \frac{{\sin \left(x_m \cdot 0.5\right)}^{2}}{\sin x_m}\\
\end{array}
\end{array}
if x < 1.00000000000000006e-9Initial program 69.5%
*-commutative69.5%
remove-double-neg69.5%
sin-neg69.5%
distribute-lft-neg-out69.5%
distribute-rgt-neg-in69.5%
associate-*l/99.5%
*-commutative99.5%
distribute-rgt-neg-in99.5%
distribute-lft-neg-out99.5%
sin-neg99.5%
remove-double-neg99.5%
associate-*l*99.4%
Simplified99.4%
*-commutative99.4%
associate-*r/69.4%
associate-/r/69.4%
div-inv69.5%
associate-/r*69.6%
pow269.6%
metadata-eval69.6%
Applied egg-rr69.6%
Taylor expanded in x around 0 65.9%
if 1.00000000000000006e-9 < x Initial program 99.2%
associate-/l*99.3%
*-commutative99.3%
associate-*l/99.1%
metadata-eval99.1%
metadata-eval99.1%
metadata-eval99.1%
metadata-eval99.1%
times-frac99.3%
*-commutative99.3%
times-frac99.2%
associate-/l*99.2%
*-commutative99.2%
neg-mul-199.2%
sin-neg99.2%
distribute-lft-neg-out99.2%
associate-*l/99.3%
Simplified99.3%
div-inv99.2%
clear-num99.3%
associate-*r*99.2%
*-commutative99.2%
associate-*r/99.3%
pow299.3%
Applied egg-rr99.3%
Final simplification72.7%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(*
x_s
(if (<= x_m 6e-12)
(/ (* x_m 0.25) 0.375)
(* (pow (sin (* x_m 0.5)) 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 tmp;
if (x_m <= 6e-12) {
tmp = (x_m * 0.25) / 0.375;
} else {
tmp = pow(sin((x_m * 0.5)), 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) :: tmp
if (x_m <= 6d-12) then
tmp = (x_m * 0.25d0) / 0.375d0
else
tmp = (sin((x_m * 0.5d0)) ** 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 tmp;
if (x_m <= 6e-12) {
tmp = (x_m * 0.25) / 0.375;
} else {
tmp = Math.pow(Math.sin((x_m * 0.5)), 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): tmp = 0 if x_m <= 6e-12: tmp = (x_m * 0.25) / 0.375 else: tmp = math.pow(math.sin((x_m * 0.5)), 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) tmp = 0.0 if (x_m <= 6e-12) tmp = Float64(Float64(x_m * 0.25) / 0.375); else tmp = Float64((sin(Float64(x_m * 0.5)) ^ 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) tmp = 0.0; if (x_m <= 6e-12) tmp = (x_m * 0.25) / 0.375; else tmp = (sin((x_m * 0.5)) ^ 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_] := N[(x$95$s * If[LessEqual[x$95$m, 6e-12], N[(N[(x$95$m * 0.25), $MachinePrecision] / 0.375), $MachinePrecision], N[(N[Power[N[Sin[N[(x$95$m * 0.5), $MachinePrecision]], $MachinePrecision], 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)
\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 6 \cdot 10^{-12}:\\
\;\;\;\;\frac{x_m \cdot 0.25}{0.375}\\
\mathbf{else}:\\
\;\;\;\;{\sin \left(x_m \cdot 0.5\right)}^{2} \cdot \frac{2.6666666666666665}{\sin x_m}\\
\end{array}
\end{array}
if x < 6.0000000000000003e-12Initial program 69.4%
*-commutative69.4%
remove-double-neg69.4%
sin-neg69.4%
distribute-lft-neg-out69.4%
distribute-rgt-neg-in69.4%
associate-*l/99.5%
*-commutative99.5%
distribute-rgt-neg-in99.5%
distribute-lft-neg-out99.5%
sin-neg99.5%
remove-double-neg99.5%
associate-*l*99.4%
Simplified99.4%
*-commutative99.4%
associate-*r/69.3%
associate-/r/69.2%
div-inv69.3%
associate-/r*69.4%
pow269.4%
metadata-eval69.4%
Applied egg-rr69.4%
Taylor expanded in x around 0 65.7%
if 6.0000000000000003e-12 < x Initial program 99.2%
associate-/l*99.3%
*-commutative99.3%
associate-*l/99.1%
metadata-eval99.1%
metadata-eval99.1%
metadata-eval99.1%
metadata-eval99.1%
times-frac99.3%
*-commutative99.3%
times-frac99.2%
associate-/l*99.2%
*-commutative99.2%
neg-mul-199.2%
sin-neg99.2%
distribute-lft-neg-out99.2%
associate-*l/99.3%
Simplified99.3%
associate-/r/99.2%
*-commutative99.2%
associate-/l*99.2%
associate-/r/99.1%
*-commutative99.1%
associate-*r*99.2%
pow299.2%
Applied egg-rr99.2%
Final simplification72.6%
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 (sin x_m)) (/ 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 * ((t_0 / sin(x_m)) * (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 * ((t_0 / sin(x_m)) * (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 * ((t_0 / Math.sin(x_m)) * (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 * ((t_0 / math.sin(x_m)) * (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(t_0 / sin(x_m)) * 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 * ((t_0 / sin(x_m)) * (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[(t$95$0 / N[Sin[x$95$m], $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{t_0}{\sin x_m} \cdot \frac{t_0}{0.375}\right)
\end{array}
\end{array}
Initial program 75.5%
associate-/l*99.4%
*-commutative99.4%
associate-*l/99.4%
metadata-eval99.4%
metadata-eval99.4%
metadata-eval99.4%
metadata-eval99.4%
times-frac99.4%
*-commutative99.4%
times-frac99.4%
associate-/l*99.4%
*-commutative99.4%
neg-mul-199.4%
sin-neg99.4%
distribute-lft-neg-out99.4%
associate-*l/99.4%
Simplified99.4%
associate-/r/99.4%
*-commutative99.4%
associate-*l/99.4%
associate-/r/99.4%
associate-*l/75.4%
div-inv75.5%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
Final simplification99.6%
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 75.5%
*-commutative75.5%
remove-double-neg75.5%
sin-neg75.5%
distribute-lft-neg-out75.5%
distribute-rgt-neg-in75.5%
associate-*l/99.4%
*-commutative99.4%
distribute-rgt-neg-in99.4%
distribute-lft-neg-out99.4%
sin-neg99.4%
remove-double-neg99.4%
associate-*l*99.4%
Simplified99.4%
Final simplification99.4%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(*
x_s
(if (<= x_m 0.000165)
(/ (* x_m 0.25) 0.375)
(/ 2.6666666666666665 (/ (sin x_m) (- 0.5 (/ (cos x_m) 2.0)))))))x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
double tmp;
if (x_m <= 0.000165) {
tmp = (x_m * 0.25) / 0.375;
} else {
tmp = 2.6666666666666665 / (sin(x_m) / (0.5 - (cos(x_m) / 2.0)));
}
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 <= 0.000165d0) then
tmp = (x_m * 0.25d0) / 0.375d0
else
tmp = 2.6666666666666665d0 / (sin(x_m) / (0.5d0 - (cos(x_m) / 2.0d0)))
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 <= 0.000165) {
tmp = (x_m * 0.25) / 0.375;
} else {
tmp = 2.6666666666666665 / (Math.sin(x_m) / (0.5 - (Math.cos(x_m) / 2.0)));
}
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 <= 0.000165: tmp = (x_m * 0.25) / 0.375 else: tmp = 2.6666666666666665 / (math.sin(x_m) / (0.5 - (math.cos(x_m) / 2.0))) 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 <= 0.000165) tmp = Float64(Float64(x_m * 0.25) / 0.375); else tmp = Float64(2.6666666666666665 / Float64(sin(x_m) / Float64(0.5 - Float64(cos(x_m) / 2.0)))); 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 <= 0.000165) tmp = (x_m * 0.25) / 0.375; else tmp = 2.6666666666666665 / (sin(x_m) / (0.5 - (cos(x_m) / 2.0))); 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, 0.000165], N[(N[(x$95$m * 0.25), $MachinePrecision] / 0.375), $MachinePrecision], N[(2.6666666666666665 / N[(N[Sin[x$95$m], $MachinePrecision] / N[(0.5 - N[(N[Cos[x$95$m], $MachinePrecision] / 2.0), $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 0.000165:\\
\;\;\;\;\frac{x_m \cdot 0.25}{0.375}\\
\mathbf{else}:\\
\;\;\;\;\frac{2.6666666666666665}{\frac{\sin x_m}{0.5 - \frac{\cos x_m}{2}}}\\
\end{array}
\end{array}
if x < 1.65e-4Initial program 69.5%
*-commutative69.5%
remove-double-neg69.5%
sin-neg69.5%
distribute-lft-neg-out69.5%
distribute-rgt-neg-in69.5%
associate-*l/99.5%
*-commutative99.5%
distribute-rgt-neg-in99.5%
distribute-lft-neg-out99.5%
sin-neg99.5%
remove-double-neg99.5%
associate-*l*99.4%
Simplified99.4%
*-commutative99.4%
associate-*r/69.4%
associate-/r/69.4%
div-inv69.5%
associate-/r*69.6%
pow269.6%
metadata-eval69.6%
Applied egg-rr69.6%
Taylor expanded in x around 0 65.9%
if 1.65e-4 < x Initial program 99.2%
*-commutative99.2%
remove-double-neg99.2%
sin-neg99.2%
distribute-lft-neg-out99.2%
distribute-rgt-neg-in99.2%
associate-*l/99.3%
*-commutative99.3%
distribute-rgt-neg-in99.3%
distribute-lft-neg-out99.3%
sin-neg99.3%
remove-double-neg99.3%
associate-*l*99.2%
Simplified99.2%
associate-*r/99.3%
associate-*r/99.1%
associate-/l*99.3%
pow299.3%
Applied egg-rr99.3%
unpow299.3%
sin-mult97.9%
Applied egg-rr97.9%
div-sub97.9%
+-inverses97.9%
cos-097.9%
metadata-eval97.9%
distribute-lft-out97.9%
metadata-eval97.9%
*-rgt-identity97.9%
Simplified97.9%
Final simplification72.4%
x_m = (fabs.f64 x)
x_s = (copysign.f64 1 x)
(FPCore (x_s x_m)
:precision binary64
(*
x_s
(if (<= x_m 0.000165)
(/ (* x_m 0.25) 0.375)
(/ (/ (- 0.5 (/ (cos x_m) 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 tmp;
if (x_m <= 0.000165) {
tmp = (x_m * 0.25) / 0.375;
} else {
tmp = ((0.5 - (cos(x_m) / 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) :: tmp
if (x_m <= 0.000165d0) then
tmp = (x_m * 0.25d0) / 0.375d0
else
tmp = ((0.5d0 - (cos(x_m) / 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 tmp;
if (x_m <= 0.000165) {
tmp = (x_m * 0.25) / 0.375;
} else {
tmp = ((0.5 - (Math.cos(x_m) / 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): tmp = 0 if x_m <= 0.000165: tmp = (x_m * 0.25) / 0.375 else: tmp = ((0.5 - (math.cos(x_m) / 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) tmp = 0.0 if (x_m <= 0.000165) tmp = Float64(Float64(x_m * 0.25) / 0.375); else tmp = Float64(Float64(Float64(0.5 - Float64(cos(x_m) / 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) tmp = 0.0; if (x_m <= 0.000165) tmp = (x_m * 0.25) / 0.375; else tmp = ((0.5 - (cos(x_m) / 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_] := N[(x$95$s * If[LessEqual[x$95$m, 0.000165], N[(N[(x$95$m * 0.25), $MachinePrecision] / 0.375), $MachinePrecision], N[(N[(N[(0.5 - N[(N[Cos[x$95$m], $MachinePrecision] / 2.0), $MachinePrecision]), $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)
\\
x_s \cdot \begin{array}{l}
\mathbf{if}\;x_m \leq 0.000165:\\
\;\;\;\;\frac{x_m \cdot 0.25}{0.375}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{0.5 - \frac{\cos x_m}{2}}{\sin x_m}}{0.375}\\
\end{array}
\end{array}
if x < 1.65e-4Initial program 69.5%
*-commutative69.5%
remove-double-neg69.5%
sin-neg69.5%
distribute-lft-neg-out69.5%
distribute-rgt-neg-in69.5%
associate-*l/99.5%
*-commutative99.5%
distribute-rgt-neg-in99.5%
distribute-lft-neg-out99.5%
sin-neg99.5%
remove-double-neg99.5%
associate-*l*99.4%
Simplified99.4%
*-commutative99.4%
associate-*r/69.4%
associate-/r/69.4%
div-inv69.5%
associate-/r*69.6%
pow269.6%
metadata-eval69.6%
Applied egg-rr69.6%
Taylor expanded in x around 0 65.9%
if 1.65e-4 < x Initial program 99.2%
*-commutative99.2%
remove-double-neg99.2%
sin-neg99.2%
distribute-lft-neg-out99.2%
distribute-rgt-neg-in99.2%
associate-*l/99.3%
*-commutative99.3%
distribute-rgt-neg-in99.3%
distribute-lft-neg-out99.3%
sin-neg99.3%
remove-double-neg99.3%
associate-*l*99.2%
Simplified99.2%
*-commutative99.2%
associate-*r/99.3%
associate-/r/99.1%
div-inv99.0%
associate-/r*99.1%
pow299.1%
metadata-eval99.1%
Applied egg-rr99.1%
unpow299.3%
sin-mult97.9%
Applied egg-rr98.1%
div-sub97.9%
+-inverses97.9%
cos-097.9%
metadata-eval97.9%
distribute-lft-out97.9%
metadata-eval97.9%
*-rgt-identity97.9%
Simplified98.1%
Final simplification72.4%
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 75.5%
associate-/l*99.4%
*-commutative99.4%
associate-*l/99.4%
metadata-eval99.4%
metadata-eval99.4%
metadata-eval99.4%
metadata-eval99.4%
times-frac99.4%
*-commutative99.4%
times-frac99.4%
associate-/l*99.4%
*-commutative99.4%
neg-mul-199.4%
sin-neg99.4%
distribute-lft-neg-out99.4%
associate-*l/99.4%
Simplified99.4%
associate-/r/99.4%
*-commutative99.4%
associate-*l/99.4%
associate-/r/99.4%
associate-*l/75.4%
div-inv75.5%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
Taylor expanded in x around 0 56.7%
Final simplification56.7%
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 75.5%
*-commutative75.5%
remove-double-neg75.5%
sin-neg75.5%
distribute-lft-neg-out75.5%
distribute-rgt-neg-in75.5%
associate-*r/99.4%
neg-mul-199.4%
*-commutative99.4%
associate-/l*99.4%
associate-/r/99.4%
*-commutative99.4%
Simplified99.4%
Taylor expanded in x around 0 56.6%
Final simplification56.6%
x_m = (fabs.f64 x) x_s = (copysign.f64 1 x) (FPCore (x_s x_m) :precision binary64 (* x_s (/ 2.6666666666666665 (+ (* x_m -0.3333333333333333) (/ 4.0 x_m)))))
x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
return x_s * (2.6666666666666665 / ((x_m * -0.3333333333333333) + (4.0 / 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
code = x_s * (2.6666666666666665d0 / ((x_m * (-0.3333333333333333d0)) + (4.0d0 / 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) {
return x_s * (2.6666666666666665 / ((x_m * -0.3333333333333333) + (4.0 / x_m)));
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): return x_s * (2.6666666666666665 / ((x_m * -0.3333333333333333) + (4.0 / x_m)))
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) return Float64(x_s * Float64(2.6666666666666665 / Float64(Float64(x_m * -0.3333333333333333) + Float64(4.0 / x_m)))) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp = code(x_s, x_m) tmp = x_s * (2.6666666666666665 / ((x_m * -0.3333333333333333) + (4.0 / 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_] := N[(x$95$s * N[(2.6666666666666665 / N[(N[(x$95$m * -0.3333333333333333), $MachinePrecision] + N[(4.0 / 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 \frac{2.6666666666666665}{x_m \cdot -0.3333333333333333 + \frac{4}{x_m}}
\end{array}
Initial program 75.5%
*-commutative75.5%
remove-double-neg75.5%
sin-neg75.5%
distribute-lft-neg-out75.5%
distribute-rgt-neg-in75.5%
associate-*l/99.4%
*-commutative99.4%
distribute-rgt-neg-in99.4%
distribute-lft-neg-out99.4%
sin-neg99.4%
remove-double-neg99.4%
associate-*l*99.4%
Simplified99.4%
associate-*r/75.5%
associate-*r/75.5%
associate-/l*75.5%
pow275.5%
Applied egg-rr75.5%
Taylor expanded in x around 0 53.4%
Taylor expanded in x around 0 53.5%
Final simplification53.5%
x_m = (fabs.f64 x) x_s = (copysign.f64 1 x) (FPCore (x_s x_m) :precision binary64 (* x_s (/ 0.5 (/ 0.75 x_m))))
x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
return x_s * (0.5 / (0.75 / 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
code = x_s * (0.5d0 / (0.75d0 / 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) {
return x_s * (0.5 / (0.75 / x_m));
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): return x_s * (0.5 / (0.75 / x_m))
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) return Float64(x_s * Float64(0.5 / Float64(0.75 / x_m))) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp = code(x_s, x_m) tmp = x_s * (0.5 / (0.75 / 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_] := N[(x$95$s * N[(0.5 / N[(0.75 / 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 \frac{0.5}{\frac{0.75}{x_m}}
\end{array}
Initial program 75.5%
associate-/l*99.4%
*-commutative99.4%
associate-*l/99.4%
metadata-eval99.4%
metadata-eval99.4%
metadata-eval99.4%
metadata-eval99.4%
times-frac99.4%
*-commutative99.4%
times-frac99.4%
associate-/l*99.4%
*-commutative99.4%
neg-mul-199.4%
sin-neg99.4%
distribute-lft-neg-out99.4%
associate-*l/99.4%
Simplified99.4%
associate-/r/99.4%
*-commutative99.4%
associate-*l/99.4%
associate-/r/99.4%
associate-*l/75.4%
div-inv75.5%
times-frac99.6%
metadata-eval99.6%
Applied egg-rr99.6%
clear-num99.4%
un-div-inv99.4%
Applied egg-rr99.4%
Taylor expanded in x around 0 56.6%
Taylor expanded in x around 0 53.2%
Final simplification53.2%
x_m = (fabs.f64 x) x_s = (copysign.f64 1 x) (FPCore (x_s x_m) :precision binary64 (* x_s (/ (* x_m 0.25) 0.375)))
x_m = fabs(x);
x_s = copysign(1.0, x);
double code(double x_s, double x_m) {
return x_s * ((x_m * 0.25) / 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 * ((x_m * 0.25d0) / 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 * ((x_m * 0.25) / 0.375);
}
x_m = math.fabs(x) x_s = math.copysign(1.0, x) def code(x_s, x_m): return x_s * ((x_m * 0.25) / 0.375)
x_m = abs(x) x_s = copysign(1.0, x) function code(x_s, x_m) return Float64(x_s * Float64(Float64(x_m * 0.25) / 0.375)) end
x_m = abs(x); x_s = sign(x) * abs(1.0); function tmp = code(x_s, x_m) tmp = x_s * ((x_m * 0.25) / 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[(N[(x$95$m * 0.25), $MachinePrecision] / 0.375), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
x_m = \left|x\right|
\\
x_s = \mathsf{copysign}\left(1, x\right)
\\
x_s \cdot \frac{x_m \cdot 0.25}{0.375}
\end{array}
Initial program 75.5%
*-commutative75.5%
remove-double-neg75.5%
sin-neg75.5%
distribute-lft-neg-out75.5%
distribute-rgt-neg-in75.5%
associate-*l/99.4%
*-commutative99.4%
distribute-rgt-neg-in99.4%
distribute-lft-neg-out99.4%
sin-neg99.4%
remove-double-neg99.4%
associate-*l*99.4%
Simplified99.4%
*-commutative99.4%
associate-*r/75.5%
associate-/r/75.4%
div-inv75.5%
associate-/r*75.6%
pow275.6%
metadata-eval75.6%
Applied egg-rr75.6%
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 75.5%
associate-/l*99.4%
*-commutative99.4%
associate-*l/99.4%
metadata-eval99.4%
metadata-eval99.4%
metadata-eval99.4%
metadata-eval99.4%
times-frac99.4%
*-commutative99.4%
times-frac99.4%
associate-/l*99.4%
*-commutative99.4%
neg-mul-199.4%
sin-neg99.4%
distribute-lft-neg-out99.4%
associate-*l/99.4%
Simplified99.4%
Taylor expanded in x around 0 53.2%
*-commutative53.2%
Simplified53.2%
Final simplification53.2%
(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 2024017
(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)))