
(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 12 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)
(pow
(cbrt
(/
(fma
0.5
(pow x -3.0)
(/ (+ 1.0 (+ (/ 0.75 (pow x 4.0)) (/ 1.875 (pow x 6.0)))) x))
(sqrt PI)))
3.0)))
double code(double x) {
return pow(exp(x), x) * pow(cbrt((fma(0.5, pow(x, -3.0), ((1.0 + ((0.75 / pow(x, 4.0)) + (1.875 / pow(x, 6.0)))) / x)) / sqrt(((double) M_PI)))), 3.0);
}
function code(x) return Float64((exp(x) ^ x) * (cbrt(Float64(fma(0.5, (x ^ -3.0), Float64(Float64(1.0 + Float64(Float64(0.75 / (x ^ 4.0)) + Float64(1.875 / (x ^ 6.0)))) / x)) / sqrt(pi))) ^ 3.0)) end
code[x_] := N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] * N[Power[N[Power[N[(N[(0.5 * N[Power[x, -3.0], $MachinePrecision] + N[(N[(1.0 + N[(N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision], 3.0], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
{\left(e^{x}\right)}^{x} \cdot {\left(\sqrt[3]{\frac{\mathsf{fma}\left(0.5, {x}^{-3}, \frac{1 + \left(\frac{0.75}{{x}^{4}} + \frac{1.875}{{x}^{6}}\right)}{x}\right)}{\sqrt{\pi}}}\right)}^{3}
\end{array}
Initial program 100.0%
Simplified100.0%
add-cube-cbrt100.0%
pow3100.0%
Applied egg-rr100.0%
Taylor expanded in x around 0 100.0%
associate-*r/100.0%
metadata-eval100.0%
associate-*r/100.0%
metadata-eval100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(pow (exp x) x)
(/
(fma
0.5
(pow x -3.0)
(/ (+ 1.0 (+ (/ 0.75 (pow x 4.0)) (/ 1.875 (pow x 6.0)))) x))
(cbrt (pow PI 1.5)))))
double code(double x) {
return pow(exp(x), x) * (fma(0.5, pow(x, -3.0), ((1.0 + ((0.75 / pow(x, 4.0)) + (1.875 / pow(x, 6.0)))) / x)) / cbrt(pow(((double) M_PI), 1.5)));
}
function code(x) return Float64((exp(x) ^ x) * Float64(fma(0.5, (x ^ -3.0), Float64(Float64(1.0 + Float64(Float64(0.75 / (x ^ 4.0)) + Float64(1.875 / (x ^ 6.0)))) / x)) / cbrt((pi ^ 1.5)))) end
code[x_] := N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] * N[(N[(0.5 * N[Power[x, -3.0], $MachinePrecision] + N[(N[(1.0 + N[(N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision] / N[Power[N[Power[Pi, 1.5], $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
{\left(e^{x}\right)}^{x} \cdot \frac{\mathsf{fma}\left(0.5, {x}^{-3}, \frac{1 + \left(\frac{0.75}{{x}^{4}} + \frac{1.875}{{x}^{6}}\right)}{x}\right)}{\sqrt[3]{{\pi}^{1.5}}}
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
add-cbrt-cube100.0%
pow1/3100.0%
add-sqr-sqrt100.0%
pow1100.0%
pow1/2100.0%
pow-prod-up100.0%
metadata-eval100.0%
Applied egg-rr100.0%
unpow1/3100.0%
Simplified100.0%
Taylor expanded in x around 0 100.0%
associate-*r/100.0%
metadata-eval100.0%
associate-*r/100.0%
metadata-eval100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(let* ((t_0 (sqrt (/ 1.0 PI))))
(*
(pow (exp x) x)
(+
(* t_0 (+ (/ 1.875 (pow x 7.0)) (/ 0.75 (pow x 5.0))))
(* t_0 (+ (/ 0.5 (pow x 3.0)) (/ 1.0 x)))))))
double code(double x) {
double t_0 = sqrt((1.0 / ((double) M_PI)));
return pow(exp(x), x) * ((t_0 * ((1.875 / pow(x, 7.0)) + (0.75 / pow(x, 5.0)))) + (t_0 * ((0.5 / pow(x, 3.0)) + (1.0 / x))));
}
public static double code(double x) {
double t_0 = Math.sqrt((1.0 / Math.PI));
return Math.pow(Math.exp(x), x) * ((t_0 * ((1.875 / Math.pow(x, 7.0)) + (0.75 / Math.pow(x, 5.0)))) + (t_0 * ((0.5 / Math.pow(x, 3.0)) + (1.0 / x))));
}
def code(x): t_0 = math.sqrt((1.0 / math.pi)) return math.pow(math.exp(x), x) * ((t_0 * ((1.875 / math.pow(x, 7.0)) + (0.75 / math.pow(x, 5.0)))) + (t_0 * ((0.5 / math.pow(x, 3.0)) + (1.0 / x))))
function code(x) t_0 = sqrt(Float64(1.0 / pi)) return Float64((exp(x) ^ x) * Float64(Float64(t_0 * Float64(Float64(1.875 / (x ^ 7.0)) + Float64(0.75 / (x ^ 5.0)))) + Float64(t_0 * Float64(Float64(0.5 / (x ^ 3.0)) + Float64(1.0 / x))))) end
function tmp = code(x) t_0 = sqrt((1.0 / pi)); tmp = (exp(x) ^ x) * ((t_0 * ((1.875 / (x ^ 7.0)) + (0.75 / (x ^ 5.0)))) + (t_0 * ((0.5 / (x ^ 3.0)) + (1.0 / x)))); end
code[x_] := Block[{t$95$0 = N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision]}, N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] * N[(N[(t$95$0 * N[(N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision] + N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$0 * N[(N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision] + N[(1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{\frac{1}{\pi}}\\
{\left(e^{x}\right)}^{x} \cdot \left(t\_0 \cdot \left(\frac{1.875}{{x}^{7}} + \frac{0.75}{{x}^{5}}\right) + t\_0 \cdot \left(\frac{0.5}{{x}^{3}} + \frac{1}{x}\right)\right)
\end{array}
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
Taylor expanded in x around 0 100.0%
+-commutative100.0%
associate-+r+100.0%
associate-+l+100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(pow (exp x) x)
(/
(fma
0.5
(pow x -3.0)
(/ (+ 1.0 (+ (/ 0.75 (pow x 4.0)) (/ 1.875 (pow x 6.0)))) x))
(sqrt PI))))
double code(double x) {
return pow(exp(x), x) * (fma(0.5, pow(x, -3.0), ((1.0 + ((0.75 / pow(x, 4.0)) + (1.875 / pow(x, 6.0)))) / x)) / sqrt(((double) M_PI)));
}
function code(x) return Float64((exp(x) ^ x) * Float64(fma(0.5, (x ^ -3.0), Float64(Float64(1.0 + Float64(Float64(0.75 / (x ^ 4.0)) + Float64(1.875 / (x ^ 6.0)))) / x)) / sqrt(pi))) end
code[x_] := N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] * N[(N[(0.5 * N[Power[x, -3.0], $MachinePrecision] + N[(N[(1.0 + N[(N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
{\left(e^{x}\right)}^{x} \cdot \frac{\mathsf{fma}\left(0.5, {x}^{-3}, \frac{1 + \left(\frac{0.75}{{x}^{4}} + \frac{1.875}{{x}^{6}}\right)}{x}\right)}{\sqrt{\pi}}
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
Taylor expanded in x around 0 100.0%
associate-*r/100.0%
metadata-eval100.0%
associate-*r/100.0%
metadata-eval100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(exp (* x x))
(*
(sqrt (/ 1.0 PI))
(+
(+ (/ 0.75 (pow x 5.0)) (/ 1.0 x))
(fma 0.5 (pow x -3.0) (/ 1.875 (pow x 7.0)))))))
double code(double x) {
return exp((x * x)) * (sqrt((1.0 / ((double) M_PI))) * (((0.75 / pow(x, 5.0)) + (1.0 / x)) + fma(0.5, pow(x, -3.0), (1.875 / pow(x, 7.0)))));
}
function code(x) return Float64(exp(Float64(x * x)) * Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(Float64(0.75 / (x ^ 5.0)) + Float64(1.0 / x)) + fma(0.5, (x ^ -3.0), Float64(1.875 / (x ^ 7.0)))))) end
code[x_] := N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision] + N[(1.0 / x), $MachinePrecision]), $MachinePrecision] + N[(0.5 * N[Power[x, -3.0], $MachinePrecision] + N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x} \cdot \left(\sqrt{\frac{1}{\pi}} \cdot \left(\left(\frac{0.75}{{x}^{5}} + \frac{1}{x}\right) + \mathsf{fma}\left(0.5, {x}^{-3}, \frac{1.875}{{x}^{7}}\right)\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
Taylor expanded in x around 0 100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (exp (pow x 2.0)) (/ (fma 0.5 (pow x -3.0) (/ (+ 1.0 (/ 0.75 (pow x 4.0))) x)) (sqrt PI))))
double code(double x) {
return exp(pow(x, 2.0)) * (fma(0.5, pow(x, -3.0), ((1.0 + (0.75 / pow(x, 4.0))) / x)) / sqrt(((double) M_PI)));
}
function code(x) return Float64(exp((x ^ 2.0)) * Float64(fma(0.5, (x ^ -3.0), Float64(Float64(1.0 + Float64(0.75 / (x ^ 4.0))) / x)) / sqrt(pi))) end
code[x_] := N[(N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision] * N[(N[(0.5 * N[Power[x, -3.0], $MachinePrecision] + N[(N[(1.0 + N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{{x}^{2}} \cdot \frac{\mathsf{fma}\left(0.5, {x}^{-3}, \frac{1 + \frac{0.75}{{x}^{4}}}{x}\right)}{\sqrt{\pi}}
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
Taylor expanded in x around inf 99.8%
Taylor expanded in x around inf 99.8%
Final simplification99.8%
(FPCore (x) :precision binary64 (* (* (sqrt (/ 1.0 PI)) (+ (/ 0.5 (pow x 3.0)) (/ 1.0 x))) (exp (pow x 2.0))))
double code(double x) {
return (sqrt((1.0 / ((double) M_PI))) * ((0.5 / pow(x, 3.0)) + (1.0 / x))) * exp(pow(x, 2.0));
}
public static double code(double x) {
return (Math.sqrt((1.0 / Math.PI)) * ((0.5 / Math.pow(x, 3.0)) + (1.0 / x))) * Math.exp(Math.pow(x, 2.0));
}
def code(x): return (math.sqrt((1.0 / math.pi)) * ((0.5 / math.pow(x, 3.0)) + (1.0 / x))) * math.exp(math.pow(x, 2.0))
function code(x) return Float64(Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(0.5 / (x ^ 3.0)) + Float64(1.0 / x))) * exp((x ^ 2.0))) end
function tmp = code(x) tmp = (sqrt((1.0 / pi)) * ((0.5 / (x ^ 3.0)) + (1.0 / x))) * exp((x ^ 2.0)); end
code[x_] := N[(N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision] + N[(1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\sqrt{\frac{1}{\pi}} \cdot \left(\frac{0.5}{{x}^{3}} + \frac{1}{x}\right)\right) \cdot e^{{x}^{2}}
\end{array}
Initial program 100.0%
Simplified100.0%
*-un-lft-identity100.0%
Applied egg-rr100.0%
*-lft-identity100.0%
Simplified100.0%
Taylor expanded in x around inf 99.8%
Taylor expanded in x around inf 99.8%
Taylor expanded in x around inf 99.8%
associate-*r*99.8%
associate-*r/99.8%
metadata-eval99.8%
distribute-rgt-out99.8%
Simplified99.8%
Final simplification99.8%
(FPCore (x) :precision binary64 (* (exp (* x x)) (* (sqrt (/ 1.0 PI)) (+ (/ 0.75 (pow x 5.0)) (/ 1.0 x)))))
double code(double x) {
return exp((x * x)) * (sqrt((1.0 / ((double) M_PI))) * ((0.75 / pow(x, 5.0)) + (1.0 / x)));
}
public static double code(double x) {
return Math.exp((x * x)) * (Math.sqrt((1.0 / Math.PI)) * ((0.75 / Math.pow(x, 5.0)) + (1.0 / x)));
}
def code(x): return math.exp((x * x)) * (math.sqrt((1.0 / math.pi)) * ((0.75 / math.pow(x, 5.0)) + (1.0 / x)))
function code(x) return Float64(exp(Float64(x * x)) * Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(0.75 / (x ^ 5.0)) + Float64(1.0 / x)))) end
function tmp = code(x) tmp = exp((x * x)) * (sqrt((1.0 / pi)) * ((0.75 / (x ^ 5.0)) + (1.0 / x))); end
code[x_] := N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision] + N[(1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x} \cdot \left(\sqrt{\frac{1}{\pi}} \cdot \left(\frac{0.75}{{x}^{5}} + \frac{1}{x}\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
Taylor expanded in x around inf 99.7%
associate-+r+99.7%
+-commutative99.7%
associate-+l+99.7%
metadata-eval99.7%
fabs-div99.7%
unpow199.7%
sqr-pow99.7%
fabs-sqr99.7%
sqr-pow99.7%
unpow199.7%
Simplified99.7%
Taylor expanded in x around inf 99.7%
associate-*r*99.7%
distribute-rgt-out99.7%
associate-*r/99.7%
metadata-eval99.7%
Simplified99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (* (exp (* x x)) (pow (* x (sqrt PI)) -1.0)))
double code(double x) {
return exp((x * x)) * pow((x * sqrt(((double) M_PI))), -1.0);
}
public static double code(double x) {
return Math.exp((x * x)) * Math.pow((x * Math.sqrt(Math.PI)), -1.0);
}
def code(x): return math.exp((x * x)) * math.pow((x * math.sqrt(math.pi)), -1.0)
function code(x) return Float64(exp(Float64(x * x)) * (Float64(x * sqrt(pi)) ^ -1.0)) end
function tmp = code(x) tmp = exp((x * x)) * ((x * sqrt(pi)) ^ -1.0); end
code[x_] := N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * N[Power[N[(x * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision], -1.0], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x} \cdot {\left(x \cdot \sqrt{\pi}\right)}^{-1}
\end{array}
Initial program 100.0%
Simplified100.0%
Taylor expanded in x around inf 99.7%
associate-+r+99.7%
+-commutative99.7%
associate-+l+99.7%
metadata-eval99.7%
fabs-div99.7%
unpow199.7%
sqr-pow99.7%
fabs-sqr99.7%
sqr-pow99.7%
unpow199.7%
Simplified99.7%
Taylor expanded in x around inf 99.7%
associate-*r*99.7%
distribute-rgt-out99.7%
associate-*r/99.7%
metadata-eval99.7%
Simplified99.7%
Taylor expanded in x around inf 99.7%
associate-*l/99.7%
*-lft-identity99.7%
Simplified99.7%
clear-num99.7%
inv-pow99.7%
sqrt-div99.7%
metadata-eval99.7%
pow1/299.7%
metadata-eval99.7%
pow-pow99.7%
pow1/399.7%
associate-/r/99.7%
/-rgt-identity99.7%
pow1/399.7%
pow-pow99.7%
metadata-eval99.7%
pow1/299.7%
Applied egg-rr99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (* (exp (* x x)) (/ (pow PI -0.5) x)))
double code(double x) {
return exp((x * x)) * (pow(((double) M_PI), -0.5) / x);
}
public static double code(double x) {
return Math.exp((x * x)) * (Math.pow(Math.PI, -0.5) / x);
}
def code(x): return math.exp((x * x)) * (math.pow(math.pi, -0.5) / x)
function code(x) return Float64(exp(Float64(x * x)) * Float64((pi ^ -0.5) / x)) end
function tmp = code(x) tmp = exp((x * x)) * ((pi ^ -0.5) / x); end
code[x_] := N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * N[(N[Power[Pi, -0.5], $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x} \cdot \frac{{\pi}^{-0.5}}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
Taylor expanded in x around inf 99.7%
associate-+r+99.7%
+-commutative99.7%
associate-+l+99.7%
metadata-eval99.7%
fabs-div99.7%
unpow199.7%
sqr-pow99.7%
fabs-sqr99.7%
sqr-pow99.7%
unpow199.7%
Simplified99.7%
Taylor expanded in x around inf 99.7%
associate-*r*99.7%
distribute-rgt-out99.7%
associate-*r/99.7%
metadata-eval99.7%
Simplified99.7%
Taylor expanded in x around inf 99.7%
associate-*l/99.7%
*-lft-identity99.7%
Simplified99.7%
*-un-lft-identity2.3%
div-inv2.3%
div-inv2.3%
inv-pow2.3%
sqrt-pow12.3%
metadata-eval2.3%
Applied egg-rr99.7%
*-lft-identity2.3%
Simplified99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (* 0.5 (/ (pow PI -0.5) x)))
double code(double x) {
return 0.5 * (pow(((double) M_PI), -0.5) / x);
}
public static double code(double x) {
return 0.5 * (Math.pow(Math.PI, -0.5) / x);
}
def code(x): return 0.5 * (math.pow(math.pi, -0.5) / x)
function code(x) return Float64(0.5 * Float64((pi ^ -0.5) / x)) end
function tmp = code(x) tmp = 0.5 * ((pi ^ -0.5) / x); end
code[x_] := N[(0.5 * N[(N[Power[Pi, -0.5], $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.5 \cdot \frac{{\pi}^{-0.5}}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
Taylor expanded in x around 0 40.7%
associate-*r*40.7%
*-commutative40.7%
*-commutative40.7%
associate-/r*41.9%
metadata-eval41.9%
fabs-div41.9%
unpow141.9%
sqr-pow41.9%
fabs-sqr41.9%
sqr-pow41.9%
unpow141.9%
associate-/r*40.7%
unpow240.7%
cube-mult40.7%
exp-to-pow40.7%
*-commutative40.7%
exp-neg41.9%
distribute-lft-neg-in41.9%
metadata-eval41.9%
*-commutative41.9%
exp-to-pow41.9%
Simplified41.9%
Taylor expanded in x around 0 2.3%
+-commutative2.3%
associate-*r*2.3%
associate-*r*2.3%
distribute-rgt-out2.3%
associate-*r/2.3%
metadata-eval2.3%
associate-*r/2.3%
metadata-eval2.3%
Simplified2.3%
Taylor expanded in x around inf 2.3%
associate-*l/2.3%
*-lft-identity2.3%
Simplified2.3%
*-un-lft-identity2.3%
div-inv2.3%
div-inv2.3%
inv-pow2.3%
sqrt-pow12.3%
metadata-eval2.3%
Applied egg-rr2.3%
*-lft-identity2.3%
Simplified2.3%
Final simplification2.3%
(FPCore (x) :precision binary64 (/ (sqrt (/ 1.0 PI)) x))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) / x;
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) / x;
}
def code(x): return math.sqrt((1.0 / math.pi)) / x
function code(x) return Float64(sqrt(Float64(1.0 / pi)) / x) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) / x; end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] / x), $MachinePrecision]
\begin{array}{l}
\\
\frac{\sqrt{\frac{1}{\pi}}}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
Taylor expanded in x around inf 99.7%
associate-+r+99.7%
+-commutative99.7%
associate-+l+99.7%
metadata-eval99.7%
fabs-div99.7%
unpow199.7%
sqr-pow99.7%
fabs-sqr99.7%
sqr-pow99.7%
unpow199.7%
Simplified99.7%
Taylor expanded in x around inf 99.7%
associate-*r*99.7%
distribute-rgt-out99.7%
associate-*r/99.7%
metadata-eval99.7%
Simplified99.7%
Taylor expanded in x around inf 99.7%
associate-*l/99.7%
*-lft-identity99.7%
Simplified99.7%
Taylor expanded in x around 0 2.3%
Final simplification2.3%
herbie shell --seed 2024043
(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)))))))