
(FPCore (x)
:precision binary64
(let* ((t_0 (/ 1.0 (fabs x)))
(t_1 (* (* t_0 t_0) t_0))
(t_2 (* (* t_1 t_0) t_0)))
(*
(* (/ 1.0 (sqrt PI)) (exp (* (fabs x) (fabs x))))
(+
(+ (+ t_0 (* (/ 1.0 2.0) t_1)) (* (/ 3.0 4.0) t_2))
(* (/ 15.0 8.0) (* (* t_2 t_0) t_0))))))
double code(double x) {
double t_0 = 1.0 / fabs(x);
double t_1 = (t_0 * t_0) * t_0;
double t_2 = (t_1 * t_0) * t_0;
return ((1.0 / sqrt(((double) M_PI))) * exp((fabs(x) * fabs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)));
}
public static double code(double x) {
double t_0 = 1.0 / Math.abs(x);
double t_1 = (t_0 * t_0) * t_0;
double t_2 = (t_1 * t_0) * t_0;
return ((1.0 / Math.sqrt(Math.PI)) * Math.exp((Math.abs(x) * Math.abs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)));
}
def code(x): t_0 = 1.0 / math.fabs(x) t_1 = (t_0 * t_0) * t_0 t_2 = (t_1 * t_0) * t_0 return ((1.0 / math.sqrt(math.pi)) * math.exp((math.fabs(x) * math.fabs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)))
function code(x) t_0 = Float64(1.0 / abs(x)) t_1 = Float64(Float64(t_0 * t_0) * t_0) t_2 = Float64(Float64(t_1 * t_0) * t_0) return Float64(Float64(Float64(1.0 / sqrt(pi)) * exp(Float64(abs(x) * abs(x)))) * Float64(Float64(Float64(t_0 + Float64(Float64(1.0 / 2.0) * t_1)) + Float64(Float64(3.0 / 4.0) * t_2)) + Float64(Float64(15.0 / 8.0) * Float64(Float64(t_2 * t_0) * t_0)))) end
function tmp = code(x) t_0 = 1.0 / abs(x); t_1 = (t_0 * t_0) * t_0; t_2 = (t_1 * t_0) * t_0; tmp = ((1.0 / sqrt(pi)) * exp((abs(x) * abs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0))); end
code[x_] := Block[{t$95$0 = N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(t$95$0 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, N[(N[(N[(1.0 / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[Exp[N[(N[Abs[x], $MachinePrecision] * N[Abs[x], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(t$95$0 + N[(N[(1.0 / 2.0), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(N[(3.0 / 4.0), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(N[(15.0 / 8.0), $MachinePrecision] * N[(N[(t$95$2 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{1}{\left|x\right|}\\
t_1 := \left(t\_0 \cdot t\_0\right) \cdot t\_0\\
t_2 := \left(t\_1 \cdot t\_0\right) \cdot t\_0\\
\left(\frac{1}{\sqrt{\pi}} \cdot e^{\left|x\right| \cdot \left|x\right|}\right) \cdot \left(\left(\left(t\_0 + \frac{1}{2} \cdot t\_1\right) + \frac{3}{4} \cdot t\_2\right) + \frac{15}{8} \cdot \left(\left(t\_2 \cdot t\_0\right) \cdot t\_0\right)\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 10 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (x)
:precision binary64
(let* ((t_0 (/ 1.0 (fabs x)))
(t_1 (* (* t_0 t_0) t_0))
(t_2 (* (* t_1 t_0) t_0)))
(*
(* (/ 1.0 (sqrt PI)) (exp (* (fabs x) (fabs x))))
(+
(+ (+ t_0 (* (/ 1.0 2.0) t_1)) (* (/ 3.0 4.0) t_2))
(* (/ 15.0 8.0) (* (* t_2 t_0) t_0))))))
double code(double x) {
double t_0 = 1.0 / fabs(x);
double t_1 = (t_0 * t_0) * t_0;
double t_2 = (t_1 * t_0) * t_0;
return ((1.0 / sqrt(((double) M_PI))) * exp((fabs(x) * fabs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)));
}
public static double code(double x) {
double t_0 = 1.0 / Math.abs(x);
double t_1 = (t_0 * t_0) * t_0;
double t_2 = (t_1 * t_0) * t_0;
return ((1.0 / Math.sqrt(Math.PI)) * Math.exp((Math.abs(x) * Math.abs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)));
}
def code(x): t_0 = 1.0 / math.fabs(x) t_1 = (t_0 * t_0) * t_0 t_2 = (t_1 * t_0) * t_0 return ((1.0 / math.sqrt(math.pi)) * math.exp((math.fabs(x) * math.fabs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)))
function code(x) t_0 = Float64(1.0 / abs(x)) t_1 = Float64(Float64(t_0 * t_0) * t_0) t_2 = Float64(Float64(t_1 * t_0) * t_0) return Float64(Float64(Float64(1.0 / sqrt(pi)) * exp(Float64(abs(x) * abs(x)))) * Float64(Float64(Float64(t_0 + Float64(Float64(1.0 / 2.0) * t_1)) + Float64(Float64(3.0 / 4.0) * t_2)) + Float64(Float64(15.0 / 8.0) * Float64(Float64(t_2 * t_0) * t_0)))) end
function tmp = code(x) t_0 = 1.0 / abs(x); t_1 = (t_0 * t_0) * t_0; t_2 = (t_1 * t_0) * t_0; tmp = ((1.0 / sqrt(pi)) * exp((abs(x) * abs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0))); end
code[x_] := Block[{t$95$0 = N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(t$95$0 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, N[(N[(N[(1.0 / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[Exp[N[(N[Abs[x], $MachinePrecision] * N[Abs[x], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(t$95$0 + N[(N[(1.0 / 2.0), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(N[(3.0 / 4.0), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(N[(15.0 / 8.0), $MachinePrecision] * N[(N[(t$95$2 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{1}{\left|x\right|}\\
t_1 := \left(t\_0 \cdot t\_0\right) \cdot t\_0\\
t_2 := \left(t\_1 \cdot t\_0\right) \cdot t\_0\\
\left(\frac{1}{\sqrt{\pi}} \cdot e^{\left|x\right| \cdot \left|x\right|}\right) \cdot \left(\left(\left(t\_0 + \frac{1}{2} \cdot t\_1\right) + \frac{3}{4} \cdot t\_2\right) + \frac{15}{8} \cdot \left(\left(t\_2 \cdot t\_0\right) \cdot t\_0\right)\right)
\end{array}
\end{array}
(FPCore (x)
:precision binary64
(let* ((t_0 (/ 1.0 (fabs x))) (t_1 (pow t_0 3.0)))
(*
(/ (pow (exp x) x) (pow (cbrt (sqrt PI)) 3.0))
(fma
1.875
(* t_1 (/ t_1 (fabs x)))
(fma 0.75 (log (exp (/ (pow x -4.0) x))) (fma 0.5 t_1 t_0))))))
double code(double x) {
double t_0 = 1.0 / fabs(x);
double t_1 = pow(t_0, 3.0);
return (pow(exp(x), x) / pow(cbrt(sqrt(((double) M_PI))), 3.0)) * fma(1.875, (t_1 * (t_1 / fabs(x))), fma(0.75, log(exp((pow(x, -4.0) / x))), fma(0.5, t_1, t_0)));
}
function code(x) t_0 = Float64(1.0 / abs(x)) t_1 = t_0 ^ 3.0 return Float64(Float64((exp(x) ^ x) / (cbrt(sqrt(pi)) ^ 3.0)) * fma(1.875, Float64(t_1 * Float64(t_1 / abs(x))), fma(0.75, log(exp(Float64((x ^ -4.0) / x))), fma(0.5, t_1, t_0)))) end
code[x_] := Block[{t$95$0 = N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[t$95$0, 3.0], $MachinePrecision]}, N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Power[N[Power[N[Sqrt[Pi], $MachinePrecision], 1/3], $MachinePrecision], 3.0], $MachinePrecision]), $MachinePrecision] * N[(1.875 * N[(t$95$1 * N[(t$95$1 / N[Abs[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.75 * N[Log[N[Exp[N[(N[Power[x, -4.0], $MachinePrecision] / x), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] + N[(0.5 * t$95$1 + t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{1}{\left|x\right|}\\
t_1 := {t\_0}^{3}\\
\frac{{\left(e^{x}\right)}^{x}}{{\left(\sqrt[3]{\sqrt{\pi}}\right)}^{3}} \cdot \mathsf{fma}\left(1.875, t\_1 \cdot \frac{t\_1}{\left|x\right|}, \mathsf{fma}\left(0.75, \log \left(e^{\frac{{x}^{-4}}{x}}\right), \mathsf{fma}\left(0.5, t\_1, t\_0\right)\right)\right)
\end{array}
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
div-inv100.0%
pow-plus100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
add-cube-cbrt100.0%
pow3100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (pow (sqrt (exp x)) (* x 2.0)) (sqrt PI)) (fma 0.75 (pow x -5.0) (fma 1.875 (pow x -7.0) (/ (+ 1.0 (/ 0.5 (* x x))) (fabs x))))))
double code(double x) {
return (pow(sqrt(exp(x)), (x * 2.0)) / sqrt(((double) M_PI))) * fma(0.75, pow(x, -5.0), fma(1.875, pow(x, -7.0), ((1.0 + (0.5 / (x * x))) / fabs(x))));
}
function code(x) return Float64(Float64((sqrt(exp(x)) ^ Float64(x * 2.0)) / sqrt(pi)) * fma(0.75, (x ^ -5.0), fma(1.875, (x ^ -7.0), Float64(Float64(1.0 + Float64(0.5 / Float64(x * x))) / abs(x))))) end
code[x_] := N[(N[(N[Power[N[Sqrt[N[Exp[x], $MachinePrecision]], $MachinePrecision], N[(x * 2.0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.75 * N[Power[x, -5.0], $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(N[(1.0 + N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Abs[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(\sqrt{e^{x}}\right)}^{\left(x \cdot 2\right)}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.75, {x}^{-5}, \mathsf{fma}\left(1.875, {x}^{-7}, \frac{1 + \frac{0.5}{x \cdot x}}{\left|x\right|}\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
exp-prod100.0%
Applied egg-rr100.0%
add-sqr-sqrt100.0%
unpow-prod-down100.0%
Applied egg-rr100.0%
pow-sqr100.0%
*-commutative100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (sqrt PI)) (fma 0.75 (pow x -5.0) (fma 1.875 (pow x -7.0) (* (+ -1.0 (* -0.5 (pow x -2.0))) (/ -1.0 x))))))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * fma(0.75, pow(x, -5.0), fma(1.875, pow(x, -7.0), ((-1.0 + (-0.5 * pow(x, -2.0))) * (-1.0 / x))));
}
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * fma(0.75, (x ^ -5.0), fma(1.875, (x ^ -7.0), Float64(Float64(-1.0 + Float64(-0.5 * (x ^ -2.0))) * Float64(-1.0 / x))))) end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.75 * N[Power[x, -5.0], $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(N[(-1.0 + N[(-0.5 * N[Power[x, -2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(-1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.75, {x}^{-5}, \mathsf{fma}\left(1.875, {x}^{-7}, \left(-1 + -0.5 \cdot {x}^{-2}\right) \cdot \frac{-1}{x}\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
exp-prod100.0%
Applied egg-rr100.0%
frac-2neg100.0%
div-inv100.0%
distribute-neg-in100.0%
metadata-eval100.0%
expm1-log1p-u100.0%
log1p-define100.0%
sub-neg100.0%
div-inv100.0%
cancel-sign-sub-inv100.0%
log1p-define100.0%
expm1-log1p-u100.0%
metadata-eval100.0%
pow2100.0%
pow-flip100.0%
metadata-eval100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (sqrt PI)) (fma 0.75 (pow x -5.0) (fma 1.875 (pow x -7.0) (/ (+ 1.0 (/ 0.5 (pow x 2.0))) x)))))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * fma(0.75, pow(x, -5.0), fma(1.875, pow(x, -7.0), ((1.0 + (0.5 / pow(x, 2.0))) / x)));
}
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * fma(0.75, (x ^ -5.0), fma(1.875, (x ^ -7.0), Float64(Float64(1.0 + Float64(0.5 / (x ^ 2.0))) / x)))) end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.75 * N[Power[x, -5.0], $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(N[(1.0 + N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.75, {x}^{-5}, \mathsf{fma}\left(1.875, {x}^{-7}, \frac{1 + \frac{0.5}{{x}^{2}}}{x}\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
exp-prod100.0%
Applied egg-rr100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
associate-/l*100.0%
add-sqr-sqrt100.0%
hypot-1-def100.0%
sqrt-div100.0%
sqrt-prod100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
hypot-1-def100.0%
sqrt-div100.0%
sqrt-prod100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
associate-*r/100.0%
hypot-undefine100.0%
hypot-undefine100.0%
rem-square-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
associate-*r/100.0%
rem-square-sqrt100.0%
associate-/r*100.0%
unpow2100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (fma 0.75 (pow x -5.0) (fma 1.875 (pow x -7.0) (+ (/ 1.0 x) (/ 0.5 (pow x 3.0)))))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * fma(0.75, pow(x, -5.0), fma(1.875, pow(x, -7.0), ((1.0 / x) + (0.5 / pow(x, 3.0)))));
}
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * fma(0.75, (x ^ -5.0), fma(1.875, (x ^ -7.0), Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0)))))) end
code[x_] := N[(N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.75 * N[Power[x, -5.0], $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(N[(1.0 / x), $MachinePrecision] + N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.75, {x}^{-5}, \mathsf{fma}\left(1.875, {x}^{-7}, \frac{1}{x} + \frac{0.5}{{x}^{3}}\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
associate-/l*100.0%
add-sqr-sqrt100.0%
hypot-1-def100.0%
sqrt-div100.0%
sqrt-prod100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
hypot-1-def100.0%
sqrt-div100.0%
sqrt-prod100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
associate-*r/100.0%
hypot-undefine100.0%
hypot-undefine100.0%
rem-square-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
associate-*r/100.0%
rem-square-sqrt100.0%
associate-/r*100.0%
unpow2100.0%
Simplified100.0%
Taylor expanded in x around inf 100.0%
metadata-eval100.0%
cancel-sign-sub-inv100.0%
associate-*r/100.0%
metadata-eval100.0%
div-sub100.0%
sub-neg100.0%
distribute-frac-neg100.0%
distribute-neg-frac100.0%
metadata-eval100.0%
associate-/r*100.0%
unpow2100.0%
unpow3100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (fma 0.75 (pow x -5.0) (fma 1.875 (pow x -7.0) (/ (+ 1.0 (* (/ 1.0 x) (/ 0.5 x))) x)))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * fma(0.75, pow(x, -5.0), fma(1.875, pow(x, -7.0), ((1.0 + ((1.0 / x) * (0.5 / x))) / x)));
}
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * fma(0.75, (x ^ -5.0), fma(1.875, (x ^ -7.0), Float64(Float64(1.0 + Float64(Float64(1.0 / x) * Float64(0.5 / x))) / x)))) end
code[x_] := N[(N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.75 * N[Power[x, -5.0], $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(N[(1.0 + N[(N[(1.0 / x), $MachinePrecision] * N[(0.5 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.75, {x}^{-5}, \mathsf{fma}\left(1.875, {x}^{-7}, \frac{1 + \frac{1}{x} \cdot \frac{0.5}{x}}{x}\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
associate-/l*100.0%
add-sqr-sqrt100.0%
hypot-1-def100.0%
sqrt-div100.0%
sqrt-prod100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
hypot-1-def100.0%
sqrt-div100.0%
sqrt-prod100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
associate-*r/100.0%
hypot-undefine100.0%
hypot-undefine100.0%
rem-square-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
associate-*r/100.0%
rem-square-sqrt100.0%
associate-/r*100.0%
unpow2100.0%
Simplified100.0%
pow2100.0%
associate-/r*100.0%
div-inv100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (fma 0.75 (pow x -5.0) (fma 1.875 (pow x -7.0) (/ 1.0 x)))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * fma(0.75, pow(x, -5.0), fma(1.875, pow(x, -7.0), (1.0 / x)));
}
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * fma(0.75, (x ^ -5.0), fma(1.875, (x ^ -7.0), Float64(1.0 / x)))) end
code[x_] := N[(N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.75 * N[Power[x, -5.0], $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.75, {x}^{-5}, \mathsf{fma}\left(1.875, {x}^{-7}, \frac{1}{x}\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
associate-/l*100.0%
add-sqr-sqrt100.0%
hypot-1-def100.0%
sqrt-div100.0%
sqrt-prod100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
hypot-1-def100.0%
sqrt-div100.0%
sqrt-prod100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
associate-*r/100.0%
hypot-undefine100.0%
hypot-undefine100.0%
rem-square-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
associate-*r/100.0%
rem-square-sqrt100.0%
associate-/r*100.0%
unpow2100.0%
Simplified100.0%
Taylor expanded in x around inf 99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (* (sqrt (/ 1.0 PI)) (+ (/ 0.5 (* (fabs x) (pow x 2.0))) (+ (/ 1.0 (fabs x)) (/ 0.75 (pow x 5.0))))))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) * ((0.5 / (fabs(x) * pow(x, 2.0))) + ((1.0 / fabs(x)) + (0.75 / pow(x, 5.0))));
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) * ((0.5 / (Math.abs(x) * Math.pow(x, 2.0))) + ((1.0 / Math.abs(x)) + (0.75 / Math.pow(x, 5.0))));
}
def code(x): return math.sqrt((1.0 / math.pi)) * ((0.5 / (math.fabs(x) * math.pow(x, 2.0))) + ((1.0 / math.fabs(x)) + (0.75 / math.pow(x, 5.0))))
function code(x) return Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(0.5 / Float64(abs(x) * (x ^ 2.0))) + Float64(Float64(1.0 / abs(x)) + Float64(0.75 / (x ^ 5.0))))) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) * ((0.5 / (abs(x) * (x ^ 2.0))) + ((1.0 / abs(x)) + (0.75 / (x ^ 5.0)))); end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(0.5 / N[(N[Abs[x], $MachinePrecision] * N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision] + N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{\pi}} \cdot \left(\frac{0.5}{\left|x\right| \cdot {x}^{2}} + \left(\frac{1}{\left|x\right|} + \frac{0.75}{{x}^{5}}\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
Taylor expanded in x around 0 2.2%
Taylor expanded in x around inf 2.2%
associate-*r*2.2%
*-commutative2.2%
+-commutative2.2%
*-commutative2.2%
associate-*r*2.2%
distribute-rgt-out2.2%
distribute-lft-out2.2%
associate-*r/2.2%
metadata-eval2.2%
Simplified2.2%
Final simplification2.2%
(FPCore (x) :precision binary64 (* (sqrt (/ 1.0 PI)) (+ (/ 1.0 (fabs x)) (/ (/ 0.5 (pow x 2.0)) (fabs x)))))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) * ((1.0 / fabs(x)) + ((0.5 / pow(x, 2.0)) / fabs(x)));
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) * ((1.0 / Math.abs(x)) + ((0.5 / Math.pow(x, 2.0)) / Math.abs(x)));
}
def code(x): return math.sqrt((1.0 / math.pi)) * ((1.0 / math.fabs(x)) + ((0.5 / math.pow(x, 2.0)) / math.fabs(x)))
function code(x) return Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(1.0 / abs(x)) + Float64(Float64(0.5 / (x ^ 2.0)) / abs(x)))) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) * ((1.0 / abs(x)) + ((0.5 / (x ^ 2.0)) / abs(x))); end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision] + N[(N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision] / N[Abs[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{\pi}} \cdot \left(\frac{1}{\left|x\right|} + \frac{\frac{0.5}{{x}^{2}}}{\left|x\right|}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
Taylor expanded in x around 0 2.2%
Taylor expanded in x around inf 2.2%
associate-*r*2.2%
*-commutative2.2%
distribute-rgt-out2.2%
+-commutative2.2%
associate-*r/2.2%
metadata-eval2.2%
associate-/r*2.2%
Simplified2.2%
Final simplification2.2%
(FPCore (x) :precision binary64 (/ (sqrt (/ 1.0 PI)) (fabs x)))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) / fabs(x);
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) / Math.abs(x);
}
def code(x): return math.sqrt((1.0 / math.pi)) / math.fabs(x)
function code(x) return Float64(sqrt(Float64(1.0 / pi)) / abs(x)) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) / abs(x); end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] / N[Abs[x], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\sqrt{\frac{1}{\pi}}}{\left|x\right|}
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
*-un-lft-identity100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
Taylor expanded in x around 0 2.2%
Taylor expanded in x around inf 2.2%
associate-*r/2.2%
*-rgt-identity2.2%
Simplified2.2%
Final simplification2.2%
herbie shell --seed 2024075
(FPCore (x)
:name "Jmat.Real.erfi, branch x greater than or equal to 5"
:precision binary64
:pre (>= x 0.5)
(* (* (/ 1.0 (sqrt PI)) (exp (* (fabs x) (fabs x)))) (+ (+ (+ (/ 1.0 (fabs x)) (* (/ 1.0 2.0) (* (* (/ 1.0 (fabs x)) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))))) (* (/ 3.0 4.0) (* (* (* (* (/ 1.0 (fabs x)) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))))) (* (/ 15.0 8.0) (* (* (* (* (* (* (/ 1.0 (fabs x)) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x))) (/ 1.0 (fabs x)))))))