
(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 0.75 (pow x -5.0) (fma 1.875 (pow x -7.0) (pow (/ x (fma 0.5 (pow x -2.0) 1.0)) -1.0)))))
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), pow((x / fma(0.5, pow(x, -2.0), 1.0)), -1.0)));
}
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * fma(0.75, (x ^ -5.0), fma(1.875, (x ^ -7.0), (Float64(x / fma(0.5, (x ^ -2.0), 1.0)) ^ -1.0)))) 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[Power[N[(x / N[(0.5 * N[Power[x, -2.0], $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision], -1.0], $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(\frac{x}{\mathsf{fma}\left(0.5, {x}^{-2}, 1\right)}\right)}^{-1}\right)\right)
\end{array}
Initial program 99.9%
Simplified99.9%
add-log-exp99.9%
*-un-lft-identity99.9%
log-prod99.9%
metadata-eval99.9%
add-log-exp99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
+-lft-identity99.9%
Simplified99.9%
exp-prod100.0%
Applied egg-rr100.0%
clear-num100.0%
inv-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
+-commutative100.0%
div-inv100.0%
fma-define100.0%
pow2100.0%
pow-flip100.0%
metadata-eval100.0%
Applied egg-rr100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
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))) 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 99.9%
Simplified99.9%
add-log-exp99.9%
*-un-lft-identity99.9%
log-prod99.9%
metadata-eval99.9%
add-log-exp99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
+-lft-identity99.9%
Simplified99.9%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr99.9%
+-lft-identity100.0%
Simplified99.9%
Taylor expanded in x around inf 99.9%
Simplified99.9%
exp-prod100.0%
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) -1.0)
(/ (+ 1.0 (/ 0.5 (* x x))) (fabs 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), ((1.0 + (0.5 / (x * x))) / fabs(x))));
}
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * fma(0.75, (x ^ -5.0), fma(1.875, Float64(Float64((x ^ -7.0) + 1.0) + -1.0), Float64(Float64(1.0 + Float64(0.5 / Float64(x * x))) / abs(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[(N[(N[Power[x, -7.0], $MachinePrecision] + 1.0), $MachinePrecision] + -1.0), $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{e^{x \cdot x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.75, {x}^{-5}, \mathsf{fma}\left(1.875, \left({x}^{-7} + 1\right) + -1, \frac{1 + \frac{0.5}{x \cdot x}}{\left|x\right|}\right)\right)
\end{array}
Initial program 99.9%
Simplified99.9%
add-log-exp99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
rem-log-exp99.9%
expm1-log1p-u99.9%
expm1-define99.9%
log1p-undefine99.9%
rem-exp-log100.0%
+-commutative100.0%
Applied egg-rr100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
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 (* (/ (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 (/ 1.0 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 * (1.0 / 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 * Float64(1.0 / 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 * N[(1.0 / x), $MachinePrecision]), $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 \left(0.5 \cdot \frac{1}{x}\right)}{x}\right)\right)
\end{array}
Initial program 99.9%
Simplified99.9%
add-log-exp99.9%
*-un-lft-identity99.9%
log-prod99.9%
metadata-eval99.9%
add-log-exp99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
+-lft-identity99.9%
Simplified99.9%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr99.9%
+-lft-identity100.0%
Simplified99.9%
Taylor expanded in x around inf 99.9%
Simplified99.9%
pow299.9%
div-inv99.9%
associate-/r*99.9%
un-div-inv99.9%
associate-*r*99.9%
Applied egg-rr99.9%
Final simplification99.9%
(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 99.9%
Simplified99.9%
add-log-exp99.9%
*-un-lft-identity99.9%
log-prod99.9%
metadata-eval99.9%
add-log-exp99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
+-lft-identity99.9%
Simplified99.9%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr99.9%
+-lft-identity100.0%
Simplified99.9%
Taylor expanded in x around inf 99.2%
metadata-eval99.2%
fabs-div99.2%
unpow-199.2%
metadata-eval99.2%
pow-sqr99.2%
fabs-sqr99.2%
pow-sqr99.2%
metadata-eval99.2%
unpow-199.2%
Simplified99.2%
Final simplification99.2%
(FPCore (x) :precision binary64 (* (/ (exp (pow x 2.0)) x) (sqrt (/ 1.0 PI))))
double code(double x) {
return (exp(pow(x, 2.0)) / x) * sqrt((1.0 / ((double) M_PI)));
}
public static double code(double x) {
return (Math.exp(Math.pow(x, 2.0)) / x) * Math.sqrt((1.0 / Math.PI));
}
def code(x): return (math.exp(math.pow(x, 2.0)) / x) * math.sqrt((1.0 / math.pi))
function code(x) return Float64(Float64(exp((x ^ 2.0)) / x) * sqrt(Float64(1.0 / pi))) end
function tmp = code(x) tmp = (exp((x ^ 2.0)) / x) * sqrt((1.0 / pi)); end
code[x_] := N[(N[(N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision] / x), $MachinePrecision] * N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{{x}^{2}}}{x} \cdot \sqrt{\frac{1}{\pi}}
\end{array}
Initial program 99.9%
Simplified99.9%
add-log-exp99.9%
*-un-lft-identity99.9%
log-prod99.9%
metadata-eval99.9%
add-log-exp99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
+-lft-identity99.9%
Simplified99.9%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr99.9%
+-lft-identity100.0%
Simplified99.9%
Taylor expanded in x around inf 99.2%
metadata-eval99.2%
fabs-div99.2%
unpow-199.2%
metadata-eval99.2%
pow-sqr99.2%
fabs-sqr99.2%
pow-sqr99.2%
metadata-eval99.2%
unpow-199.2%
Simplified99.2%
Taylor expanded in x around inf 99.1%
Final simplification99.1%
(FPCore (x) :precision binary64 (* (sqrt (/ 1.0 PI)) (/ 1.875 (pow x 7.0))))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) * (1.875 / pow(x, 7.0));
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) * (1.875 / Math.pow(x, 7.0));
}
def code(x): return math.sqrt((1.0 / math.pi)) * (1.875 / math.pow(x, 7.0))
function code(x) return Float64(sqrt(Float64(1.0 / pi)) * Float64(1.875 / (x ^ 7.0))) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) * (1.875 / (x ^ 7.0)); end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{\pi}} \cdot \frac{1.875}{{x}^{7}}
\end{array}
Initial program 99.9%
Simplified99.9%
add-log-exp99.9%
*-un-lft-identity99.9%
log-prod99.9%
metadata-eval99.9%
add-log-exp99.9%
inv-pow99.9%
pow-pow99.9%
add-sqr-sqrt99.9%
fabs-sqr99.9%
add-sqr-sqrt99.9%
metadata-eval99.9%
Applied egg-rr99.9%
+-lft-identity99.9%
Simplified99.9%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr99.9%
+-lft-identity100.0%
Simplified99.9%
Taylor expanded in x around inf 99.2%
metadata-eval99.2%
fabs-div99.2%
unpow-199.2%
metadata-eval99.2%
pow-sqr99.2%
fabs-sqr99.2%
pow-sqr99.2%
metadata-eval99.2%
unpow-199.2%
Simplified99.2%
Taylor expanded in x around 0 1.8%
associate-*r*1.8%
*-commutative1.8%
associate-*r/1.8%
metadata-eval1.8%
Simplified1.8%
Final simplification1.8%
herbie shell --seed 2024076
(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)))))))