
(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 5 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
(*
(/ (pow (exp x) x) (* x (sqrt PI)))
(+
1.0
(+
(* 3.0 (log (cbrt (pow (exp 0.75) (pow x -4.0)))))
(+ (/ 0.5 (* x x)) (* 3.0 (log (cbrt (exp (/ 1.875 (pow x 6.0)))))))))))
double code(double x) {
return (pow(exp(x), x) / (x * sqrt(((double) M_PI)))) * (1.0 + ((3.0 * log(cbrt(pow(exp(0.75), pow(x, -4.0))))) + ((0.5 / (x * x)) + (3.0 * log(cbrt(exp((1.875 / pow(x, 6.0)))))))));
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / (x * Math.sqrt(Math.PI))) * (1.0 + ((3.0 * Math.log(Math.cbrt(Math.pow(Math.exp(0.75), Math.pow(x, -4.0))))) + ((0.5 / (x * x)) + (3.0 * Math.log(Math.cbrt(Math.exp((1.875 / Math.pow(x, 6.0)))))))));
}
function code(x) return Float64(Float64((exp(x) ^ x) / Float64(x * sqrt(pi))) * Float64(1.0 + Float64(Float64(3.0 * log(cbrt((exp(0.75) ^ (x ^ -4.0))))) + Float64(Float64(0.5 / Float64(x * x)) + Float64(3.0 * log(cbrt(exp(Float64(1.875 / (x ^ 6.0)))))))))) end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[(x * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(1.0 + N[(N[(3.0 * N[Log[N[Power[N[Power[N[Exp[0.75], $MachinePrecision], N[Power[x, -4.0], $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + N[(3.0 * N[Log[N[Power[N[Exp[N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{x \cdot \sqrt{\pi}} \cdot \left(1 + \left(3 \cdot \log \left(\sqrt[3]{{\left(e^{0.75}\right)}^{\left({x}^{-4}\right)}}\right) + \left(\frac{0.5}{x \cdot x} + 3 \cdot \log \left(\sqrt[3]{e^{\frac{1.875}{{x}^{6}}}}\right)\right)\right)\right)
\end{array}
Initial program 99.9%
Simplified100.0%
Taylor expanded in x around 0 100.0%
unpow1100.0%
sqr-pow100.0%
fabs-sqr100.0%
sqr-pow100.0%
unpow1100.0%
*-commutative100.0%
Simplified100.0%
add-log-exp100.0%
add-cube-cbrt100.0%
log-prod100.0%
div-inv100.0%
exp-prod100.0%
pow-flip100.0%
metadata-eval100.0%
div-inv100.0%
exp-prod100.0%
pow-flip100.0%
metadata-eval100.0%
Applied egg-rr100.0%
log-prod100.0%
count-2100.0%
distribute-lft1-in100.0%
metadata-eval100.0%
Simplified100.0%
add-log-exp100.0%
add-cube-cbrt100.0%
log-prod100.0%
Applied egg-rr100.0%
log-prod100.0%
count-2100.0%
distribute-lft1-in100.0%
metadata-eval100.0%
Simplified100.0%
Taylor expanded in x around 0 100.0%
unpow1/3100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(/
(pow (exp x) x)
(exp (* (* 3.0 (log (* x (sqrt PI)))) 0.3333333333333333)))
(+
1.0
(+
(+ (/ 0.5 (* x x)) (* 3.0 (log (cbrt (exp (/ 1.875 (pow x 6.0)))))))
(* 0.75 (pow x -4.0))))))
double code(double x) {
return (pow(exp(x), x) / exp(((3.0 * log((x * sqrt(((double) M_PI))))) * 0.3333333333333333))) * (1.0 + (((0.5 / (x * x)) + (3.0 * log(cbrt(exp((1.875 / pow(x, 6.0))))))) + (0.75 * pow(x, -4.0))));
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / Math.exp(((3.0 * Math.log((x * Math.sqrt(Math.PI)))) * 0.3333333333333333))) * (1.0 + (((0.5 / (x * x)) + (3.0 * Math.log(Math.cbrt(Math.exp((1.875 / Math.pow(x, 6.0))))))) + (0.75 * Math.pow(x, -4.0))));
}
function code(x) return Float64(Float64((exp(x) ^ x) / exp(Float64(Float64(3.0 * log(Float64(x * sqrt(pi)))) * 0.3333333333333333))) * Float64(1.0 + Float64(Float64(Float64(0.5 / Float64(x * x)) + Float64(3.0 * log(cbrt(exp(Float64(1.875 / (x ^ 6.0))))))) + Float64(0.75 * (x ^ -4.0))))) end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Exp[N[(N[(3.0 * N[Log[N[(x * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 0.3333333333333333), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 + N[(N[(N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + N[(3.0 * N[Log[N[Power[N[Exp[N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.75 * N[Power[x, -4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{e^{\left(3 \cdot \log \left(x \cdot \sqrt{\pi}\right)\right) \cdot 0.3333333333333333}} \cdot \left(1 + \left(\left(\frac{0.5}{x \cdot x} + 3 \cdot \log \left(\sqrt[3]{e^{\frac{1.875}{{x}^{6}}}}\right)\right) + 0.75 \cdot {x}^{-4}\right)\right)
\end{array}
Initial program 99.9%
Simplified100.0%
add-cbrt-cube30.1%
pow1/330.1%
pow-to-exp30.0%
pow330.0%
metadata-eval30.0%
log-pow100.0%
metadata-eval100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
add-log-exp100.0%
add-cube-cbrt100.0%
log-prod100.0%
div-inv100.0%
exp-prod100.0%
pow-flip100.0%
metadata-eval100.0%
div-inv100.0%
exp-prod100.0%
pow-flip100.0%
metadata-eval100.0%
Applied egg-rr100.0%
log-prod100.0%
count-2100.0%
distribute-lft1-in100.0%
metadata-eval100.0%
Simplified100.0%
clear-num100.0%
associate-/r/100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Taylor expanded in x around 0 100.0%
unpow1/3100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(/ (pow (exp x) x) (expm1 (log1p (* x (sqrt PI)))))
(+
1.0
(+
(* 0.75 (pow x -4.0))
(+ (/ 0.5 (* x x)) (* 3.0 (/ 0.625 (pow x 6.0))))))))
double code(double x) {
return (pow(exp(x), x) / expm1(log1p((x * sqrt(((double) M_PI)))))) * (1.0 + ((0.75 * pow(x, -4.0)) + ((0.5 / (x * x)) + (3.0 * (0.625 / pow(x, 6.0))))));
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / Math.expm1(Math.log1p((x * Math.sqrt(Math.PI))))) * (1.0 + ((0.75 * Math.pow(x, -4.0)) + ((0.5 / (x * x)) + (3.0 * (0.625 / Math.pow(x, 6.0))))));
}
def code(x): return (math.pow(math.exp(x), x) / math.expm1(math.log1p((x * math.sqrt(math.pi))))) * (1.0 + ((0.75 * math.pow(x, -4.0)) + ((0.5 / (x * x)) + (3.0 * (0.625 / math.pow(x, 6.0))))))
function code(x) return Float64(Float64((exp(x) ^ x) / expm1(log1p(Float64(x * sqrt(pi))))) * Float64(1.0 + Float64(Float64(0.75 * (x ^ -4.0)) + Float64(Float64(0.5 / Float64(x * x)) + Float64(3.0 * Float64(0.625 / (x ^ 6.0))))))) end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[(Exp[N[Log[1 + N[(x * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]] - 1), $MachinePrecision]), $MachinePrecision] * N[(1.0 + N[(N[(0.75 * N[Power[x, -4.0], $MachinePrecision]), $MachinePrecision] + N[(N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + N[(3.0 * N[(0.625 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\mathsf{expm1}\left(\mathsf{log1p}\left(x \cdot \sqrt{\pi}\right)\right)} \cdot \left(1 + \left(0.75 \cdot {x}^{-4} + \left(\frac{0.5}{x \cdot x} + 3 \cdot \frac{0.625}{{x}^{6}}\right)\right)\right)
\end{array}
Initial program 99.9%
Simplified100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
expm1-log1p-u100.0%
Applied egg-rr100.0%
add-log-exp100.0%
add-cube-cbrt100.0%
log-prod100.0%
div-inv100.0%
exp-prod100.0%
pow-flip100.0%
metadata-eval100.0%
div-inv100.0%
exp-prod100.0%
pow-flip100.0%
metadata-eval100.0%
Applied egg-rr100.0%
log-prod100.0%
count-2100.0%
distribute-lft1-in100.0%
metadata-eval100.0%
Simplified100.0%
clear-num100.0%
associate-/r/100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Taylor expanded in x around 0 100.0%
log-pow100.0%
rem-log-exp100.0%
associate-*r/100.0%
metadata-eval100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(/ (pow (exp x) x) (* x (sqrt PI)))
(+
1.0
(+
(* 0.75 (pow x -4.0))
(+ (/ 0.5 (* x x)) (* 3.0 (/ 0.625 (pow x 6.0))))))))
double code(double x) {
return (pow(exp(x), x) / (x * sqrt(((double) M_PI)))) * (1.0 + ((0.75 * pow(x, -4.0)) + ((0.5 / (x * x)) + (3.0 * (0.625 / pow(x, 6.0))))));
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / (x * Math.sqrt(Math.PI))) * (1.0 + ((0.75 * Math.pow(x, -4.0)) + ((0.5 / (x * x)) + (3.0 * (0.625 / Math.pow(x, 6.0))))));
}
def code(x): return (math.pow(math.exp(x), x) / (x * math.sqrt(math.pi))) * (1.0 + ((0.75 * math.pow(x, -4.0)) + ((0.5 / (x * x)) + (3.0 * (0.625 / math.pow(x, 6.0))))))
function code(x) return Float64(Float64((exp(x) ^ x) / Float64(x * sqrt(pi))) * Float64(1.0 + Float64(Float64(0.75 * (x ^ -4.0)) + Float64(Float64(0.5 / Float64(x * x)) + Float64(3.0 * Float64(0.625 / (x ^ 6.0))))))) end
function tmp = code(x) tmp = ((exp(x) ^ x) / (x * sqrt(pi))) * (1.0 + ((0.75 * (x ^ -4.0)) + ((0.5 / (x * x)) + (3.0 * (0.625 / (x ^ 6.0)))))); end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[(x * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(1.0 + N[(N[(0.75 * N[Power[x, -4.0], $MachinePrecision]), $MachinePrecision] + N[(N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + N[(3.0 * N[(0.625 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{x \cdot \sqrt{\pi}} \cdot \left(1 + \left(0.75 \cdot {x}^{-4} + \left(\frac{0.5}{x \cdot x} + 3 \cdot \frac{0.625}{{x}^{6}}\right)\right)\right)
\end{array}
Initial program 99.9%
Simplified100.0%
Taylor expanded in x around 0 100.0%
unpow1100.0%
sqr-pow100.0%
fabs-sqr100.0%
sqr-pow100.0%
unpow1100.0%
*-commutative100.0%
Simplified100.0%
add-log-exp100.0%
add-cube-cbrt100.0%
log-prod100.0%
div-inv100.0%
exp-prod100.0%
pow-flip100.0%
metadata-eval100.0%
div-inv100.0%
exp-prod100.0%
pow-flip100.0%
metadata-eval100.0%
Applied egg-rr100.0%
log-prod100.0%
count-2100.0%
distribute-lft1-in100.0%
metadata-eval100.0%
Simplified100.0%
clear-num100.0%
associate-/r/100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Taylor expanded in x around 0 100.0%
log-pow100.0%
rem-log-exp100.0%
associate-*r/100.0%
metadata-eval100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (* x (sqrt PI))) (+ 1.0 (+ (/ 0.5 (* x x)) (* 0.75 (pow x -4.0))))))
double code(double x) {
return (pow(exp(x), x) / (x * sqrt(((double) M_PI)))) * (1.0 + ((0.5 / (x * x)) + (0.75 * pow(x, -4.0))));
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / (x * Math.sqrt(Math.PI))) * (1.0 + ((0.5 / (x * x)) + (0.75 * Math.pow(x, -4.0))));
}
def code(x): return (math.pow(math.exp(x), x) / (x * math.sqrt(math.pi))) * (1.0 + ((0.5 / (x * x)) + (0.75 * math.pow(x, -4.0))))
function code(x) return Float64(Float64((exp(x) ^ x) / Float64(x * sqrt(pi))) * Float64(1.0 + Float64(Float64(0.5 / Float64(x * x)) + Float64(0.75 * (x ^ -4.0))))) end
function tmp = code(x) tmp = ((exp(x) ^ x) / (x * sqrt(pi))) * (1.0 + ((0.5 / (x * x)) + (0.75 * (x ^ -4.0)))); end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[(x * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(1.0 + N[(N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + N[(0.75 * N[Power[x, -4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{x \cdot \sqrt{\pi}} \cdot \left(1 + \left(\frac{0.5}{x \cdot x} + 0.75 \cdot {x}^{-4}\right)\right)
\end{array}
Initial program 99.9%
Simplified100.0%
Taylor expanded in x around 0 100.0%
unpow1100.0%
sqr-pow100.0%
fabs-sqr100.0%
sqr-pow100.0%
unpow1100.0%
*-commutative100.0%
Simplified100.0%
add-log-exp100.0%
add-cube-cbrt100.0%
log-prod100.0%
div-inv100.0%
exp-prod100.0%
pow-flip100.0%
metadata-eval100.0%
div-inv100.0%
exp-prod100.0%
pow-flip100.0%
metadata-eval100.0%
Applied egg-rr100.0%
log-prod100.0%
count-2100.0%
distribute-lft1-in100.0%
metadata-eval100.0%
Simplified100.0%
clear-num100.0%
associate-/r/100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
Final simplification99.7%
herbie shell --seed 2023313
(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)))))))