
(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 9 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) (* (fabs x) (sqrt PI))) (+ (* 3.0 (log (cbrt (exp (/ 0.75 (pow x 4.0)))))) (+ (/ 0.5 (* x x)) (+ 1.0 (/ 1.875 (pow x 6.0)))))))
double code(double x) {
return (pow(exp(x), x) / (fabs(x) * sqrt(((double) M_PI)))) * ((3.0 * log(cbrt(exp((0.75 / pow(x, 4.0)))))) + ((0.5 / (x * x)) + (1.0 + (1.875 / pow(x, 6.0)))));
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / (Math.abs(x) * Math.sqrt(Math.PI))) * ((3.0 * Math.log(Math.cbrt(Math.exp((0.75 / Math.pow(x, 4.0)))))) + ((0.5 / (x * x)) + (1.0 + (1.875 / Math.pow(x, 6.0)))));
}
function code(x) return Float64(Float64((exp(x) ^ x) / Float64(abs(x) * sqrt(pi))) * Float64(Float64(3.0 * log(cbrt(exp(Float64(0.75 / (x ^ 4.0)))))) + Float64(Float64(0.5 / Float64(x * x)) + Float64(1.0 + Float64(1.875 / (x ^ 6.0)))))) end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[(N[Abs[x], $MachinePrecision] * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[(3.0 * N[Log[N[Power[N[Exp[N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 1/3], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + N[(1.0 + N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\left|x\right| \cdot \sqrt{\pi}} \cdot \left(3 \cdot \log \left(\sqrt[3]{e^{\frac{0.75}{{x}^{4}}}}\right) + \left(\frac{0.5}{x \cdot x} + \left(1 + \frac{1.875}{{x}^{6}}\right)\right)\right)
\end{array}
Initial program 99.9%
Simplified100.0%
log1p-expm1-u100.0%
log1p-udef100.0%
div-inv100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
add-cube-cbrt100.0%
log-prod100.0%
pow2100.0%
add-exp-log100.0%
log1p-def100.0%
log1p-expm1-u100.0%
exp-prod100.0%
add-exp-log100.0%
log1p-def100.0%
log1p-expm1-u100.0%
exp-prod100.0%
Applied egg-rr100.0%
log-pow100.0%
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 (* (+ (+ (/ 1.0 x) (/ 0.5 (pow x 3.0))) (* (pow x -5.0) (+ 0.75 (/ (/ 1.875 x) x)))) (/ (pow (exp x) x) (sqrt PI))))
double code(double x) {
return (((1.0 / x) + (0.5 / pow(x, 3.0))) + (pow(x, -5.0) * (0.75 + ((1.875 / x) / x)))) * (pow(exp(x), x) / sqrt(((double) M_PI)));
}
public static double code(double x) {
return (((1.0 / x) + (0.5 / Math.pow(x, 3.0))) + (Math.pow(x, -5.0) * (0.75 + ((1.875 / x) / x)))) * (Math.pow(Math.exp(x), x) / Math.sqrt(Math.PI));
}
def code(x): return (((1.0 / x) + (0.5 / math.pow(x, 3.0))) + (math.pow(x, -5.0) * (0.75 + ((1.875 / x) / x)))) * (math.pow(math.exp(x), x) / math.sqrt(math.pi))
function code(x) return Float64(Float64(Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0))) + Float64((x ^ -5.0) * Float64(0.75 + Float64(Float64(1.875 / x) / x)))) * Float64((exp(x) ^ x) / sqrt(pi))) end
function tmp = code(x) tmp = (((1.0 / x) + (0.5 / (x ^ 3.0))) + ((x ^ -5.0) * (0.75 + ((1.875 / x) / x)))) * ((exp(x) ^ x) / sqrt(pi)); end
code[x_] := N[(N[(N[(N[(1.0 / x), $MachinePrecision] + N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[Power[x, -5.0], $MachinePrecision] * N[(0.75 + N[(N[(1.875 / x), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right) + {x}^{-5} \cdot \left(0.75 + \frac{\frac{1.875}{x}}{x}\right)\right) \cdot \frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}}
\end{array}
Initial program 99.9%
Simplified100.0%
metadata-eval100.0%
metadata-eval100.0%
pow-prod-up100.0%
pow3100.0%
metadata-eval100.0%
pow2100.0%
associate-*l*100.0%
associate-*l*100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
inv-pow100.0%
associate-*r*100.0%
clear-num100.0%
un-div-inv100.0%
Applied egg-rr100.0%
pow-prod-up100.0%
metadata-eval100.0%
expm1-log1p-u100.0%
expm1-udef100.0%
Applied egg-rr100.0%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Taylor expanded in x around 0 100.0%
unpow198.6%
sqr-pow98.6%
fabs-sqr98.6%
sqr-pow98.6%
unpow198.6%
associate-*r/98.6%
metadata-eval98.6%
associate-/r*98.6%
unpow198.6%
sqr-pow98.6%
fabs-sqr98.6%
sqr-pow98.6%
unpow198.6%
associate-/r*98.6%
unpow298.6%
unpow398.6%
Simplified100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (sqrt PI)) (+ (+ (/ 1.0 x) (/ 0.5 (pow x 3.0))) (/ 1.875 (pow x 7.0)))))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * (((1.0 / x) + (0.5 / pow(x, 3.0))) + (1.875 / pow(x, 7.0)));
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / Math.sqrt(Math.PI)) * (((1.0 / x) + (0.5 / Math.pow(x, 3.0))) + (1.875 / Math.pow(x, 7.0)));
}
def code(x): return (math.pow(math.exp(x), x) / math.sqrt(math.pi)) * (((1.0 / x) + (0.5 / math.pow(x, 3.0))) + (1.875 / math.pow(x, 7.0)))
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * Float64(Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0))) + Float64(1.875 / (x ^ 7.0)))) end
function tmp = code(x) tmp = ((exp(x) ^ x) / sqrt(pi)) * (((1.0 / x) + (0.5 / (x ^ 3.0))) + (1.875 / (x ^ 7.0))); end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(1.0 / x), $MachinePrecision] + N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \left(\left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right) + \frac{1.875}{{x}^{7}}\right)
\end{array}
Initial program 99.9%
Simplified100.0%
*-un-lft-identity100.0%
*-commutative100.0%
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 98.6%
Taylor expanded in x around 0 98.6%
unpow198.6%
sqr-pow98.6%
fabs-sqr98.6%
sqr-pow98.6%
unpow198.6%
associate-*r/98.6%
metadata-eval98.6%
associate-/r*98.6%
unpow198.6%
sqr-pow98.6%
fabs-sqr98.6%
sqr-pow98.6%
unpow198.6%
associate-/r*98.6%
unpow298.6%
unpow398.6%
Simplified98.6%
Final simplification98.6%
(FPCore (x) :precision binary64 (* (+ (+ (/ 1.0 x) (/ 0.5 (pow x 3.0))) (/ 1.875 (pow x 7.0))) (/ (exp (* x x)) (sqrt PI))))
double code(double x) {
return (((1.0 / x) + (0.5 / pow(x, 3.0))) + (1.875 / pow(x, 7.0))) * (exp((x * x)) / sqrt(((double) M_PI)));
}
public static double code(double x) {
return (((1.0 / x) + (0.5 / Math.pow(x, 3.0))) + (1.875 / Math.pow(x, 7.0))) * (Math.exp((x * x)) / Math.sqrt(Math.PI));
}
def code(x): return (((1.0 / x) + (0.5 / math.pow(x, 3.0))) + (1.875 / math.pow(x, 7.0))) * (math.exp((x * x)) / math.sqrt(math.pi))
function code(x) return Float64(Float64(Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0))) + Float64(1.875 / (x ^ 7.0))) * Float64(exp(Float64(x * x)) / sqrt(pi))) end
function tmp = code(x) tmp = (((1.0 / x) + (0.5 / (x ^ 3.0))) + (1.875 / (x ^ 7.0))) * (exp((x * x)) / sqrt(pi)); end
code[x_] := N[(N[(N[(N[(1.0 / x), $MachinePrecision] + N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right) + \frac{1.875}{{x}^{7}}\right) \cdot \frac{e^{x \cdot x}}{\sqrt{\pi}}
\end{array}
Initial program 99.9%
Simplified100.0%
*-un-lft-identity100.0%
*-commutative100.0%
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 98.6%
Taylor expanded in x around 0 98.6%
unpow198.6%
sqr-pow98.6%
fabs-sqr98.6%
sqr-pow98.6%
unpow198.6%
associate-*r/98.6%
metadata-eval98.6%
associate-/r*98.6%
unpow198.6%
sqr-pow98.6%
fabs-sqr98.6%
sqr-pow98.6%
unpow198.6%
associate-/r*98.6%
unpow298.6%
unpow398.6%
Simplified98.6%
pow-exp98.6%
Applied egg-rr98.6%
Final simplification98.6%
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (+ (/ 1.0 x) (* (pow x -5.0) (+ 0.75 (/ (/ 1.875 x) x))))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * ((1.0 / x) + (pow(x, -5.0) * (0.75 + ((1.875 / x) / x))));
}
public static double code(double x) {
return (Math.exp((x * x)) / Math.sqrt(Math.PI)) * ((1.0 / x) + (Math.pow(x, -5.0) * (0.75 + ((1.875 / x) / x))));
}
def code(x): return (math.exp((x * x)) / math.sqrt(math.pi)) * ((1.0 / x) + (math.pow(x, -5.0) * (0.75 + ((1.875 / x) / x))))
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * Float64(Float64(1.0 / x) + Float64((x ^ -5.0) * Float64(0.75 + Float64(Float64(1.875 / x) / x))))) end
function tmp = code(x) tmp = (exp((x * x)) / sqrt(pi)) * ((1.0 / x) + ((x ^ -5.0) * (0.75 + ((1.875 / x) / x)))); end
code[x_] := N[(N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 / x), $MachinePrecision] + N[(N[Power[x, -5.0], $MachinePrecision] * N[(0.75 + N[(N[(1.875 / x), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \left(\frac{1}{x} + {x}^{-5} \cdot \left(0.75 + \frac{\frac{1.875}{x}}{x}\right)\right)
\end{array}
Initial program 99.9%
Simplified100.0%
metadata-eval100.0%
metadata-eval100.0%
pow-prod-up100.0%
pow3100.0%
metadata-eval100.0%
pow2100.0%
associate-*l*100.0%
associate-*l*100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
inv-pow100.0%
associate-*r*100.0%
clear-num100.0%
un-div-inv100.0%
Applied egg-rr100.0%
pow-prod-up100.0%
metadata-eval100.0%
expm1-log1p-u100.0%
expm1-udef100.0%
Applied egg-rr100.0%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Taylor expanded in x around inf 98.6%
unpow198.6%
sqr-pow98.6%
fabs-sqr98.6%
sqr-pow98.6%
unpow198.6%
Simplified98.6%
pow-exp98.6%
Applied egg-rr98.6%
Final simplification98.6%
(FPCore (x) :precision binary64 (/ (pow (exp x) x) (* x (sqrt PI))))
double code(double x) {
return pow(exp(x), x) / (x * sqrt(((double) M_PI)));
}
public static double code(double x) {
return Math.pow(Math.exp(x), x) / (x * Math.sqrt(Math.PI));
}
def code(x): return math.pow(math.exp(x), x) / (x * math.sqrt(math.pi))
function code(x) return Float64((exp(x) ^ x) / Float64(x * sqrt(pi))) end
function tmp = code(x) tmp = (exp(x) ^ x) / (x * sqrt(pi)); end
code[x_] := N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[(x * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{x \cdot \sqrt{\pi}}
\end{array}
Initial program 99.9%
Simplified100.0%
*-un-lft-identity100.0%
*-commutative100.0%
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 inf 98.6%
Taylor expanded in x around inf 98.4%
unpow298.4%
Simplified98.4%
associate-*r/98.4%
add-sqr-sqrt98.4%
fabs-sqr98.4%
add-sqr-sqrt98.4%
associate-*r/98.4%
sqrt-div98.4%
metadata-eval98.4%
frac-times98.4%
*-un-lft-identity98.4%
pow-exp98.4%
Applied egg-rr98.4%
Final simplification98.4%
(FPCore (x) :precision binary64 (* (sqrt (/ 1.0 PI)) (/ (+ (* x x) 1.0) (fabs x))))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) * (((x * x) + 1.0) / fabs(x));
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) * (((x * x) + 1.0) / Math.abs(x));
}
def code(x): return math.sqrt((1.0 / math.pi)) * (((x * x) + 1.0) / math.fabs(x))
function code(x) return Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(Float64(x * x) + 1.0) / abs(x))) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) * (((x * x) + 1.0) / abs(x)); end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(N[(x * x), $MachinePrecision] + 1.0), $MachinePrecision] / N[Abs[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{\pi}} \cdot \frac{x \cdot x + 1}{\left|x\right|}
\end{array}
Initial program 99.9%
Simplified100.0%
*-un-lft-identity100.0%
*-commutative100.0%
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 inf 98.6%
Taylor expanded in x around inf 98.4%
unpow298.4%
Simplified98.4%
Taylor expanded in x around 0 53.2%
unpow253.2%
Simplified53.2%
Final simplification53.2%
(FPCore (x) :precision binary64 (* (sqrt (/ 1.0 PI)) (+ (/ 1.0 x) (/ x (/ x x)))))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) * ((1.0 / x) + (x / (x / x)));
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) * ((1.0 / x) + (x / (x / x)));
}
def code(x): return math.sqrt((1.0 / math.pi)) * ((1.0 / x) + (x / (x / x)))
function code(x) return Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(1.0 / x) + Float64(x / Float64(x / x)))) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) * ((1.0 / x) + (x / (x / x))); end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(1.0 / x), $MachinePrecision] + N[(x / N[(x / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{\pi}} \cdot \left(\frac{1}{x} + \frac{x}{\frac{x}{x}}\right)
\end{array}
Initial program 99.9%
Simplified100.0%
*-un-lft-identity100.0%
*-commutative100.0%
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 inf 98.6%
Taylor expanded in x around inf 98.4%
unpow298.4%
Simplified98.4%
Taylor expanded in x around 0 53.2%
+-commutative53.2%
unpow253.2%
associate-/l*5.7%
rem-square-sqrt5.7%
fabs-sqr5.7%
rem-square-sqrt5.7%
rem-square-sqrt5.7%
fabs-sqr5.7%
rem-square-sqrt5.7%
Simplified5.7%
Final simplification5.7%
(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 99.9%
Simplified100.0%
*-un-lft-identity100.0%
*-commutative100.0%
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 inf 98.6%
Taylor expanded in x around inf 98.4%
unpow298.4%
Simplified98.4%
Taylor expanded in x around 0 2.5%
associate-*r/2.5%
*-rgt-identity2.5%
rem-square-sqrt2.5%
fabs-sqr2.5%
rem-square-sqrt2.5%
Simplified2.5%
Final simplification2.5%
herbie shell --seed 2023283
(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)))))))