
(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 7 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) (sqrt PI)) (fma 0.5 (pow x -3.0) (/ (+ (/ 1.875 (pow x 6.0)) (+ 1.0 (/ 0.75 (pow x 4.0)))) x))))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * fma(0.5, pow(x, -3.0), (((1.875 / pow(x, 6.0)) + (1.0 + (0.75 / pow(x, 4.0)))) / x));
}
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * fma(0.5, (x ^ -3.0), Float64(Float64(Float64(1.875 / (x ^ 6.0)) + Float64(1.0 + Float64(0.75 / (x ^ 4.0)))) / x))) end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.5 * N[Power[x, -3.0], $MachinePrecision] + N[(N[(N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision] + N[(1.0 + N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.5, {x}^{-3}, \frac{\frac{1.875}{{x}^{6}} + \left(1 + \frac{0.75}{{x}^{4}}\right)}{x}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
fma-undefine100.0%
+-commutative100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
distribute-rgt-in100.0%
*-un-lft-identity100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
clear-num100.0%
un-div-inv100.0%
+-commutative100.0%
fma-define100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
/-rgt-identity100.0%
Applied egg-rr100.0%
*-rgt-identity100.0%
associate-/l*100.0%
distribute-rgt1-in100.0%
+-commutative100.0%
associate-*r/100.0%
*-rgt-identity100.0%
+-commutative100.0%
fma-undefine100.0%
associate-+l+100.0%
fma-define100.0%
Simplified100.0%
Taylor expanded in x around inf 100.0%
associate-*r/100.0%
metadata-eval100.0%
metadata-eval100.0%
associate-*r/100.0%
associate-+r+100.0%
+-commutative100.0%
associate-*r/100.0%
metadata-eval100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(/ (pow (exp x) x) (sqrt PI))
(/
(+
(/ (+ 0.75 (/ 1.875 (pow x 2.0))) (pow x 4.0))
(+ 1.0 (/ 0.5 (pow x 2.0))))
x)))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * ((((0.75 + (1.875 / pow(x, 2.0))) / pow(x, 4.0)) + (1.0 + (0.5 / pow(x, 2.0)))) / x);
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / Math.sqrt(Math.PI)) * ((((0.75 + (1.875 / Math.pow(x, 2.0))) / Math.pow(x, 4.0)) + (1.0 + (0.5 / Math.pow(x, 2.0)))) / x);
}
def code(x): return (math.pow(math.exp(x), x) / math.sqrt(math.pi)) * ((((0.75 + (1.875 / math.pow(x, 2.0))) / math.pow(x, 4.0)) + (1.0 + (0.5 / math.pow(x, 2.0)))) / x)
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * Float64(Float64(Float64(Float64(0.75 + Float64(1.875 / (x ^ 2.0))) / (x ^ 4.0)) + Float64(1.0 + Float64(0.5 / (x ^ 2.0)))) / x)) end
function tmp = code(x) tmp = ((exp(x) ^ x) / sqrt(pi)) * ((((0.75 + (1.875 / (x ^ 2.0))) / (x ^ 4.0)) + (1.0 + (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[(N[(N[(N[(0.75 + N[(1.875 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision] + N[(1.0 + N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \frac{\frac{0.75 + \frac{1.875}{{x}^{2}}}{{x}^{4}} + \left(1 + \frac{0.5}{{x}^{2}}\right)}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
fma-undefine100.0%
+-commutative100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
distribute-rgt-in100.0%
*-un-lft-identity100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
clear-num100.0%
un-div-inv100.0%
+-commutative100.0%
fma-define100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
/-rgt-identity100.0%
Applied egg-rr100.0%
*-rgt-identity100.0%
associate-/l*100.0%
distribute-rgt1-in100.0%
+-commutative100.0%
associate-*r/100.0%
*-rgt-identity100.0%
+-commutative100.0%
fma-undefine100.0%
associate-+l+100.0%
fma-define100.0%
Simplified100.0%
Taylor expanded in x around -inf 100.0%
associate-*r/100.0%
mul-1-neg100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (sqrt PI)) (/ (+ 1.0 (+ (/ 0.75 (pow x 4.0)) (/ 0.5 (pow x 2.0)))) x)))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * ((1.0 + ((0.75 / pow(x, 4.0)) + (0.5 / pow(x, 2.0)))) / x);
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / Math.sqrt(Math.PI)) * ((1.0 + ((0.75 / Math.pow(x, 4.0)) + (0.5 / Math.pow(x, 2.0)))) / x);
}
def code(x): return (math.pow(math.exp(x), x) / math.sqrt(math.pi)) * ((1.0 + ((0.75 / math.pow(x, 4.0)) + (0.5 / math.pow(x, 2.0)))) / x)
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * Float64(Float64(1.0 + Float64(Float64(0.75 / (x ^ 4.0)) + Float64(0.5 / (x ^ 2.0)))) / x)) end
function tmp = code(x) tmp = ((exp(x) ^ x) / sqrt(pi)) * ((1.0 + ((0.75 / (x ^ 4.0)) + (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[(N[(1.0 + N[(N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision] + N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \frac{1 + \left(\frac{0.75}{{x}^{4}} + \frac{0.5}{{x}^{2}}\right)}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
fma-undefine100.0%
+-commutative100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
distribute-rgt-in100.0%
*-un-lft-identity100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
clear-num100.0%
un-div-inv100.0%
+-commutative100.0%
fma-define100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
/-rgt-identity100.0%
Applied egg-rr100.0%
*-rgt-identity100.0%
associate-/l*100.0%
distribute-rgt1-in100.0%
+-commutative100.0%
associate-*r/100.0%
*-rgt-identity100.0%
+-commutative100.0%
fma-undefine100.0%
associate-+l+100.0%
fma-define100.0%
Simplified100.0%
Taylor expanded in x around inf 99.7%
+-commutative99.7%
associate-*r/99.7%
metadata-eval99.7%
Simplified99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (sqrt PI)) (fma 0.5 (pow x -3.0) (/ 1.0 x))))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * fma(0.5, pow(x, -3.0), (1.0 / x));
}
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * fma(0.5, (x ^ -3.0), Float64(1.0 / x))) end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.5 * N[Power[x, -3.0], $MachinePrecision] + N[(1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.5, {x}^{-3}, \frac{1}{x}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
fma-undefine100.0%
+-commutative100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
distribute-rgt-in100.0%
*-un-lft-identity100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
clear-num100.0%
un-div-inv100.0%
+-commutative100.0%
fma-define100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
/-rgt-identity100.0%
Applied egg-rr100.0%
*-rgt-identity100.0%
associate-/l*100.0%
distribute-rgt1-in100.0%
+-commutative100.0%
associate-*r/100.0%
*-rgt-identity100.0%
+-commutative100.0%
fma-undefine100.0%
associate-+l+100.0%
fma-define100.0%
Simplified100.0%
Taylor expanded in x around inf 99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (sqrt PI)) (/ (+ 1.0 (/ 0.5 (pow x 2.0))) x)))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * ((1.0 + (0.5 / pow(x, 2.0))) / x);
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / Math.sqrt(Math.PI)) * ((1.0 + (0.5 / Math.pow(x, 2.0))) / x);
}
def code(x): return (math.pow(math.exp(x), x) / math.sqrt(math.pi)) * ((1.0 + (0.5 / math.pow(x, 2.0))) / x)
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * Float64(Float64(1.0 + Float64(0.5 / (x ^ 2.0))) / x)) end
function tmp = code(x) tmp = ((exp(x) ^ x) / sqrt(pi)) * ((1.0 + (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[(N[(1.0 + N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \frac{1 + \frac{0.5}{{x}^{2}}}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
fma-undefine100.0%
+-commutative100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
distribute-rgt-in100.0%
*-un-lft-identity100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
clear-num100.0%
un-div-inv100.0%
+-commutative100.0%
fma-define100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
/-rgt-identity100.0%
Applied egg-rr100.0%
*-rgt-identity100.0%
associate-/l*100.0%
distribute-rgt1-in100.0%
+-commutative100.0%
associate-*r/100.0%
*-rgt-identity100.0%
+-commutative100.0%
fma-undefine100.0%
associate-+l+100.0%
fma-define100.0%
Simplified100.0%
Taylor expanded in x around inf 99.7%
associate-*r/99.7%
metadata-eval99.7%
Simplified99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (sqrt PI)) (/ 0.5 (pow x 3.0))))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * (0.5 / pow(x, 3.0));
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / Math.sqrt(Math.PI)) * (0.5 / Math.pow(x, 3.0));
}
def code(x): return (math.pow(math.exp(x), x) / math.sqrt(math.pi)) * (0.5 / math.pow(x, 3.0))
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * Float64(0.5 / (x ^ 3.0))) end
function tmp = code(x) tmp = ((exp(x) ^ x) / sqrt(pi)) * (0.5 / (x ^ 3.0)); end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \frac{0.5}{{x}^{3}}
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
fma-undefine100.0%
+-commutative100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Taylor expanded in x around 0 38.7%
rem-square-sqrt38.7%
fabs-sqr38.7%
rem-square-sqrt38.7%
pow-plus38.7%
metadata-eval38.7%
Simplified38.7%
Taylor expanded in x around inf 35.2%
Final simplification35.2%
(FPCore (x) :precision binary64 (* 1.875 (/ (sqrt (/ 1.0 PI)) (pow x 7.0))))
double code(double x) {
return 1.875 * (sqrt((1.0 / ((double) M_PI))) / pow(x, 7.0));
}
public static double code(double x) {
return 1.875 * (Math.sqrt((1.0 / Math.PI)) / Math.pow(x, 7.0));
}
def code(x): return 1.875 * (math.sqrt((1.0 / math.pi)) / math.pow(x, 7.0))
function code(x) return Float64(1.875 * Float64(sqrt(Float64(1.0 / pi)) / (x ^ 7.0))) end
function tmp = code(x) tmp = 1.875 * (sqrt((1.0 / pi)) / (x ^ 7.0)); end
code[x_] := N[(1.875 * N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
1.875 \cdot \frac{\sqrt{\frac{1}{\pi}}}{{x}^{7}}
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
fma-undefine100.0%
+-commutative100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Taylor expanded in x around 0 38.7%
rem-square-sqrt38.7%
fabs-sqr38.7%
rem-square-sqrt38.7%
pow-plus38.7%
metadata-eval38.7%
Simplified38.7%
Taylor expanded in x around 0 1.7%
associate-*l/1.7%
*-lft-identity1.7%
Simplified1.7%
Final simplification1.7%
herbie shell --seed 2024051
(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)))))))