
(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 (* (/ (exp (* x x)) (sqrt PI)) (fma 0.75 (pow x -5.0) (fma 1.875 (pow x -7.0) (/ (+ 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 + (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, (x ^ -7.0), 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[Power[x, -7.0], $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, {x}^{-7}, \frac{1 + \frac{0.5}{x \cdot x}}{\left|x\right|}\right)\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%
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%
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) (+ (/ 1.0 x) (* 1.875 (pow x -7.0))))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * fma(0.75, pow(x, -5.0), ((1.0 / x) + (1.875 * pow(x, -7.0))));
}
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * fma(0.75, (x ^ -5.0), Float64(Float64(1.0 / x) + Float64(1.875 * (x ^ -7.0))))) 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[(N[(1.0 / x), $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.75, {x}^{-5}, \frac{1}{x} + 1.875 \cdot {x}^{-7}\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%
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%
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%
Taylor expanded in x around inf 99.4%
fma-undefine99.4%
+-commutative99.4%
add-sqr-sqrt99.4%
fabs-sqr99.4%
add-sqr-sqrt99.4%
Applied egg-rr99.4%
Final simplification99.4%
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (fma 0.75 (pow x -5.0) (/ 1.0 (fabs x)))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * fma(0.75, pow(x, -5.0), (1.0 / fabs(x)));
}
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * fma(0.75, (x ^ -5.0), Float64(1.0 / 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[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.75, {x}^{-5}, \frac{1}{\left|x\right|}\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%
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%
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%
Taylor expanded in x around inf 99.4%
Taylor expanded in x around inf 99.4%
Final simplification99.4%
(FPCore (x) :precision binary64 (* (exp (pow x 2.0)) (/ (sqrt (/ 1.0 PI)) (fabs x))))
double code(double x) {
return exp(pow(x, 2.0)) * (sqrt((1.0 / ((double) M_PI))) / fabs(x));
}
public static double code(double x) {
return Math.exp(Math.pow(x, 2.0)) * (Math.sqrt((1.0 / Math.PI)) / Math.abs(x));
}
def code(x): return math.exp(math.pow(x, 2.0)) * (math.sqrt((1.0 / math.pi)) / math.fabs(x))
function code(x) return Float64(exp((x ^ 2.0)) * Float64(sqrt(Float64(1.0 / pi)) / abs(x))) end
function tmp = code(x) tmp = exp((x ^ 2.0)) * (sqrt((1.0 / pi)) / abs(x)); end
code[x_] := N[(N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision] * N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] / N[Abs[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{{x}^{2}} \cdot \frac{\sqrt{\frac{1}{\pi}}}{\left|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%
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%
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%
Taylor expanded in x around inf 99.4%
associate-*r/99.4%
*-commutative99.4%
associate-/l*99.4%
Simplified99.4%
Final simplification99.4%
(FPCore (x) :precision binary64 (/ (* 0.9375 (sqrt (/ (pow x 8.0) PI))) (pow x 7.0)))
double code(double x) {
return (0.9375 * sqrt((pow(x, 8.0) / ((double) M_PI)))) / pow(x, 7.0);
}
public static double code(double x) {
return (0.9375 * Math.sqrt((Math.pow(x, 8.0) / Math.PI))) / Math.pow(x, 7.0);
}
def code(x): return (0.9375 * math.sqrt((math.pow(x, 8.0) / math.pi))) / math.pow(x, 7.0)
function code(x) return Float64(Float64(0.9375 * sqrt(Float64((x ^ 8.0) / pi))) / (x ^ 7.0)) end
function tmp = code(x) tmp = (0.9375 * sqrt(((x ^ 8.0) / pi))) / (x ^ 7.0); end
code[x_] := N[(N[(0.9375 * N[Sqrt[N[(N[Power[x, 8.0], $MachinePrecision] / Pi), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{0.9375 \cdot \sqrt{\frac{{x}^{8}}{\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%
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%
Taylor expanded in x around 0 0.7%
Simplified0.7%
Taylor expanded in x around inf 0.7%
add-sqr-sqrt0.7%
sqrt-unprod2.4%
*-commutative2.4%
*-commutative2.4%
swap-sqr2.4%
add-sqr-sqrt2.4%
pow-prod-up2.4%
metadata-eval2.4%
Applied egg-rr2.4%
associate-*l/2.4%
*-lft-identity2.4%
Simplified2.4%
Final simplification2.4%
(FPCore (x) :precision binary64 (sqrt (* (/ (pow x -14.0) PI) 3.515625)))
double code(double x) {
return sqrt(((pow(x, -14.0) / ((double) M_PI)) * 3.515625));
}
public static double code(double x) {
return Math.sqrt(((Math.pow(x, -14.0) / Math.PI) * 3.515625));
}
def code(x): return math.sqrt(((math.pow(x, -14.0) / math.pi) * 3.515625))
function code(x) return sqrt(Float64(Float64((x ^ -14.0) / pi) * 3.515625)) end
function tmp = code(x) tmp = sqrt((((x ^ -14.0) / pi) * 3.515625)); end
code[x_] := N[Sqrt[N[(N[(N[Power[x, -14.0], $MachinePrecision] / Pi), $MachinePrecision] * 3.515625), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{{x}^{-14}}{\pi} \cdot 3.515625}
\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%
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%
Taylor expanded in x around 0 1.8%
associate-*l/1.8%
associate-/l*1.8%
associate-*r*1.8%
metadata-eval1.8%
Simplified1.8%
add-sqr-sqrt1.8%
sqrt-unprod1.7%
*-commutative1.7%
*-commutative1.7%
swap-sqr1.7%
Applied egg-rr1.7%
associate-*l/1.7%
*-lft-identity1.7%
Simplified1.7%
Final simplification1.7%
(FPCore (x) :precision binary64 (* 0.9375 (/ (pow x -3.0) (sqrt PI))))
double code(double x) {
return 0.9375 * (pow(x, -3.0) / sqrt(((double) M_PI)));
}
public static double code(double x) {
return 0.9375 * (Math.pow(x, -3.0) / Math.sqrt(Math.PI));
}
def code(x): return 0.9375 * (math.pow(x, -3.0) / math.sqrt(math.pi))
function code(x) return Float64(0.9375 * Float64((x ^ -3.0) / sqrt(pi))) end
function tmp = code(x) tmp = 0.9375 * ((x ^ -3.0) / sqrt(pi)); end
code[x_] := N[(0.9375 * N[(N[Power[x, -3.0], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.9375 \cdot \frac{{x}^{-3}}{\sqrt{\pi}}
\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%
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%
Taylor expanded in x around 0 0.7%
Simplified0.7%
Taylor expanded in x around inf 1.9%
associate-*r*1.9%
*-commutative1.9%
associate-*r/1.9%
metadata-eval1.9%
Simplified1.9%
*-commutative1.9%
sqrt-div1.9%
metadata-eval1.9%
un-div-inv1.9%
div-inv1.9%
pow-flip1.9%
metadata-eval1.9%
Applied egg-rr1.9%
associate-/l*1.9%
Simplified1.9%
Final simplification1.9%
herbie shell --seed 2024077
(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)))))))