
(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 10 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
(let* ((t_0 (/ 1.0 (fabs x))))
(*
(fma
0.75
(pow t_0 5.0)
(fma 1.875 (pow t_0 7.0) (/ (+ 1.0 (/ 0.5 (* x x))) (fabs x))))
(/ (pow (exp x) x) (pow (cbrt (sqrt PI)) 3.0)))))
double code(double x) {
double t_0 = 1.0 / fabs(x);
return fma(0.75, pow(t_0, 5.0), fma(1.875, pow(t_0, 7.0), ((1.0 + (0.5 / (x * x))) / fabs(x)))) * (pow(exp(x), x) / pow(cbrt(sqrt(((double) M_PI))), 3.0));
}
function code(x) t_0 = Float64(1.0 / abs(x)) return Float64(fma(0.75, (t_0 ^ 5.0), fma(1.875, (t_0 ^ 7.0), Float64(Float64(1.0 + Float64(0.5 / Float64(x * x))) / abs(x)))) * Float64((exp(x) ^ x) / (cbrt(sqrt(pi)) ^ 3.0))) end
code[x_] := Block[{t$95$0 = N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision]}, N[(N[(0.75 * N[Power[t$95$0, 5.0], $MachinePrecision] + N[(1.875 * N[Power[t$95$0, 7.0], $MachinePrecision] + N[(N[(1.0 + N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Abs[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Power[N[Power[N[Sqrt[Pi], $MachinePrecision], 1/3], $MachinePrecision], 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{1}{\left|x\right|}\\
\mathsf{fma}\left(0.75, {t_0}^{5}, \mathsf{fma}\left(1.875, {t_0}^{7}, \frac{1 + \frac{0.5}{x \cdot x}}{\left|x\right|}\right)\right) \cdot \frac{{\left(e^{x}\right)}^{x}}{{\left(\sqrt[3]{\sqrt{\pi}}\right)}^{3}}
\end{array}
\end{array}
Initial program 100.0%
Simplified100.0%
add-cube-cbrt100.0%
pow3100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (pow (cbrt (sqrt PI)) 3.0)) (fma 0.75 (pow (/ 1.0 (fabs x)) 5.0) (fma 1.875 (pow x -7.0) (/ (+ 1.0 (/ 0.5 (* x x))) (fabs x))))))
double code(double x) {
return (pow(exp(x), x) / pow(cbrt(sqrt(((double) M_PI))), 3.0)) * fma(0.75, pow((1.0 / fabs(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(x) ^ x) / (cbrt(sqrt(pi)) ^ 3.0)) * fma(0.75, (Float64(1.0 / abs(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[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Power[N[Power[N[Sqrt[Pi], $MachinePrecision], 1/3], $MachinePrecision], 3.0], $MachinePrecision]), $MachinePrecision] * N[(0.75 * N[Power[N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision], 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{{\left(e^{x}\right)}^{x}}{{\left(\sqrt[3]{\sqrt{\pi}}\right)}^{3}} \cdot \mathsf{fma}\left(0.75, {\left(\frac{1}{\left|x\right|}\right)}^{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%
expm1-log1p-u100.0%
expm1-udef100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
add-cube-cbrt100.0%
pow3100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (fma 0.75 (pow x -5.0) (fma 1.875 (pow x -7.0) (/ (+ 1.0 (/ 0.5 (* x x))) (fabs x)))) (/ (pow (exp x) x) (sqrt PI))))
double code(double x) {
return fma(0.75, pow(x, -5.0), fma(1.875, pow(x, -7.0), ((1.0 + (0.5 / (x * x))) / fabs(x)))) * (pow(exp(x), x) / sqrt(((double) M_PI)));
}
function code(x) return Float64(fma(0.75, (x ^ -5.0), fma(1.875, (x ^ -7.0), Float64(Float64(1.0 + Float64(0.5 / Float64(x * x))) / abs(x)))) * Float64((exp(x) ^ x) / sqrt(pi))) end
code[x_] := N[(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] * N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\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) \cdot \frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}}
\end{array}
Initial program 100.0%
Simplified100.0%
expm1-log1p-u100.0%
expm1-udef100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
expm1-log1p-u100.0%
expm1-udef100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (+ (+ 1.0 (* x (sqrt PI))) -1.0)) (+ 1.0 (+ (/ 0.75 (pow x 4.0)) (+ (/ 0.5 (* x x)) (/ 1.875 (pow x 6.0)))))))
double code(double x) {
return (pow(exp(x), x) / ((1.0 + (x * sqrt(((double) M_PI)))) + -1.0)) * (1.0 + ((0.75 / pow(x, 4.0)) + ((0.5 / (x * x)) + (1.875 / pow(x, 6.0)))));
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / ((1.0 + (x * Math.sqrt(Math.PI))) + -1.0)) * (1.0 + ((0.75 / Math.pow(x, 4.0)) + ((0.5 / (x * x)) + (1.875 / Math.pow(x, 6.0)))));
}
def code(x): return (math.pow(math.exp(x), x) / ((1.0 + (x * math.sqrt(math.pi))) + -1.0)) * (1.0 + ((0.75 / math.pow(x, 4.0)) + ((0.5 / (x * x)) + (1.875 / math.pow(x, 6.0)))))
function code(x) return Float64(Float64((exp(x) ^ x) / Float64(Float64(1.0 + Float64(x * sqrt(pi))) + -1.0)) * Float64(1.0 + Float64(Float64(0.75 / (x ^ 4.0)) + Float64(Float64(0.5 / Float64(x * x)) + Float64(1.875 / (x ^ 6.0)))))) end
function tmp = code(x) tmp = ((exp(x) ^ x) / ((1.0 + (x * sqrt(pi))) + -1.0)) * (1.0 + ((0.75 / (x ^ 4.0)) + ((0.5 / (x * x)) + (1.875 / (x ^ 6.0))))); end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[(N[(1.0 + N[(x * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision] * N[(1.0 + N[(N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision] + N[(N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\left(1 + x \cdot \sqrt{\pi}\right) + -1} \cdot \left(1 + \left(\frac{0.75}{{x}^{4}} + \left(\frac{0.5}{x \cdot x} + \frac{1.875}{{x}^{6}}\right)\right)\right)
\end{array}
Initial program 100.0%
Simplified99.6%
add-sqr-sqrt99.6%
sqrt-div99.6%
sqrt-pow199.6%
metadata-eval99.6%
add-sqr-sqrt99.6%
fabs-sqr99.6%
add-sqr-sqrt99.6%
sqrt-div99.6%
sqrt-pow199.6%
metadata-eval99.6%
add-sqr-sqrt99.6%
fabs-sqr99.6%
add-sqr-sqrt99.6%
Applied egg-rr99.6%
associate-*l/99.6%
associate-*r/99.6%
rem-square-sqrt99.6%
associate-/r*99.6%
pow-sqr99.6%
metadata-eval99.6%
Simplified99.6%
add-sqr-sqrt99.6%
fabs-sqr99.6%
add-sqr-sqrt99.6%
expm1-log1p-u99.6%
Applied egg-rr99.6%
expm1-udef99.6%
log1p-udef99.6%
rem-exp-log99.6%
Applied egg-rr99.6%
Final simplification99.6%
(FPCore (x) :precision binary64 (* (+ 1.0 (+ (/ 0.75 (pow x 4.0)) (+ (/ 0.5 (* x x)) (/ 1.875 (pow x 6.0))))) (/ (pow (exp x) x) (* x (sqrt PI)))))
double code(double x) {
return (1.0 + ((0.75 / pow(x, 4.0)) + ((0.5 / (x * x)) + (1.875 / pow(x, 6.0))))) * (pow(exp(x), x) / (x * sqrt(((double) M_PI))));
}
public static double code(double x) {
return (1.0 + ((0.75 / Math.pow(x, 4.0)) + ((0.5 / (x * x)) + (1.875 / Math.pow(x, 6.0))))) * (Math.pow(Math.exp(x), x) / (x * Math.sqrt(Math.PI)));
}
def code(x): return (1.0 + ((0.75 / math.pow(x, 4.0)) + ((0.5 / (x * x)) + (1.875 / math.pow(x, 6.0))))) * (math.pow(math.exp(x), x) / (x * math.sqrt(math.pi)))
function code(x) return Float64(Float64(1.0 + Float64(Float64(0.75 / (x ^ 4.0)) + Float64(Float64(0.5 / Float64(x * x)) + Float64(1.875 / (x ^ 6.0))))) * Float64((exp(x) ^ x) / Float64(x * sqrt(pi)))) end
function tmp = code(x) tmp = (1.0 + ((0.75 / (x ^ 4.0)) + ((0.5 / (x * x)) + (1.875 / (x ^ 6.0))))) * ((exp(x) ^ x) / (x * sqrt(pi))); end
code[x_] := N[(N[(1.0 + N[(N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision] + N[(N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[(x * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(1 + \left(\frac{0.75}{{x}^{4}} + \left(\frac{0.5}{x \cdot x} + \frac{1.875}{{x}^{6}}\right)\right)\right) \cdot \frac{{\left(e^{x}\right)}^{x}}{x \cdot \sqrt{\pi}}
\end{array}
Initial program 100.0%
Simplified99.6%
add-sqr-sqrt99.6%
sqrt-div99.6%
sqrt-pow199.6%
metadata-eval99.6%
add-sqr-sqrt99.6%
fabs-sqr99.6%
add-sqr-sqrt99.6%
sqrt-div99.6%
sqrt-pow199.6%
metadata-eval99.6%
add-sqr-sqrt99.6%
fabs-sqr99.6%
add-sqr-sqrt99.6%
Applied egg-rr99.6%
associate-*l/99.6%
associate-*r/99.6%
rem-square-sqrt99.6%
associate-/r*99.6%
pow-sqr99.6%
metadata-eval99.6%
Simplified99.6%
Taylor expanded in x around 0 99.6%
unpow199.6%
metadata-eval99.6%
pow-sqr99.6%
unpow1/299.6%
unpow1/299.6%
fabs-sqr99.6%
unpow1/299.6%
unpow1/299.6%
pow-sqr99.6%
metadata-eval99.6%
unpow199.6%
Simplified99.6%
Final simplification99.6%
(FPCore (x) :precision binary64 (* (+ 1.0 (+ (/ 0.75 (pow x 4.0)) (+ (/ 0.5 (* x x)) (/ 1.875 (pow x 6.0))))) (/ (pow PI -0.5) x)))
double code(double x) {
return (1.0 + ((0.75 / pow(x, 4.0)) + ((0.5 / (x * x)) + (1.875 / pow(x, 6.0))))) * (pow(((double) M_PI), -0.5) / x);
}
public static double code(double x) {
return (1.0 + ((0.75 / Math.pow(x, 4.0)) + ((0.5 / (x * x)) + (1.875 / Math.pow(x, 6.0))))) * (Math.pow(Math.PI, -0.5) / x);
}
def code(x): return (1.0 + ((0.75 / math.pow(x, 4.0)) + ((0.5 / (x * x)) + (1.875 / math.pow(x, 6.0))))) * (math.pow(math.pi, -0.5) / x)
function code(x) return Float64(Float64(1.0 + Float64(Float64(0.75 / (x ^ 4.0)) + Float64(Float64(0.5 / Float64(x * x)) + Float64(1.875 / (x ^ 6.0))))) * Float64((pi ^ -0.5) / x)) end
function tmp = code(x) tmp = (1.0 + ((0.75 / (x ^ 4.0)) + ((0.5 / (x * x)) + (1.875 / (x ^ 6.0))))) * ((pi ^ -0.5) / x); end
code[x_] := N[(N[(1.0 + N[(N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision] + N[(N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[Power[Pi, -0.5], $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(1 + \left(\frac{0.75}{{x}^{4}} + \left(\frac{0.5}{x \cdot x} + \frac{1.875}{{x}^{6}}\right)\right)\right) \cdot \frac{{\pi}^{-0.5}}{x}
\end{array}
Initial program 100.0%
Simplified99.6%
add-sqr-sqrt99.6%
sqrt-div99.6%
sqrt-pow199.6%
metadata-eval99.6%
add-sqr-sqrt99.6%
fabs-sqr99.6%
add-sqr-sqrt99.6%
sqrt-div99.6%
sqrt-pow199.6%
metadata-eval99.6%
add-sqr-sqrt99.6%
fabs-sqr99.6%
add-sqr-sqrt99.6%
Applied egg-rr99.6%
associate-*l/99.6%
associate-*r/99.6%
rem-square-sqrt99.6%
associate-/r*99.6%
pow-sqr99.6%
metadata-eval99.6%
Simplified99.6%
Taylor expanded in x around 0 2.3%
expm1-log1p-u2.3%
expm1-udef1.7%
*-commutative1.7%
add-sqr-sqrt1.7%
fabs-sqr1.7%
add-sqr-sqrt1.7%
associate-/r*1.7%
inv-pow1.7%
sqrt-pow21.7%
metadata-eval1.7%
Applied egg-rr1.7%
expm1-def2.3%
expm1-log1p2.3%
Simplified2.3%
Final simplification2.3%
(FPCore (x) :precision binary64 (* (sqrt (/ 1.0 PI)) (+ (+ (/ 1.0 x) (/ 0.5 (pow x 3.0))) (/ 1.875 (pow x 7.0)))))
double code(double x) {
return sqrt((1.0 / ((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.sqrt((1.0 / Math.PI)) * (((1.0 / x) + (0.5 / Math.pow(x, 3.0))) + (1.875 / Math.pow(x, 7.0)));
}
def code(x): return math.sqrt((1.0 / math.pi)) * (((1.0 / x) + (0.5 / math.pow(x, 3.0))) + (1.875 / math.pow(x, 7.0)))
function code(x) return Float64(sqrt(Float64(1.0 / 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 = sqrt((1.0 / pi)) * (((1.0 / x) + (0.5 / (x ^ 3.0))) + (1.875 / (x ^ 7.0))); end
code[x_] := N[(N[Sqrt[N[(1.0 / 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}
\\
\sqrt{\frac{1}{\pi}} \cdot \left(\left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right) + \frac{1.875}{{x}^{7}}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
expm1-log1p-u100.0%
expm1-udef100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Taylor expanded in x around 0 2.3%
Taylor expanded in x around 0 2.3%
+-commutative2.3%
associate-+r+2.3%
Simplified2.3%
Taylor expanded in x around inf 2.3%
associate-*r/2.3%
metadata-eval2.3%
Simplified2.3%
Final simplification2.3%
(FPCore (x) :precision binary64 (* (sqrt (/ 1.0 PI)) (+ (/ 1.0 x) (/ 0.75 (pow x 5.0)))))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) * ((1.0 / x) + (0.75 / pow(x, 5.0)));
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) * ((1.0 / x) + (0.75 / Math.pow(x, 5.0)));
}
def code(x): return math.sqrt((1.0 / math.pi)) * ((1.0 / x) + (0.75 / math.pow(x, 5.0)))
function code(x) return Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(1.0 / x) + Float64(0.75 / (x ^ 5.0)))) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) * ((1.0 / x) + (0.75 / (x ^ 5.0))); end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(1.0 / x), $MachinePrecision] + N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{\pi}} \cdot \left(\frac{1}{x} + \frac{0.75}{{x}^{5}}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
expm1-log1p-u100.0%
expm1-udef100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Taylor expanded in x around 0 2.3%
Taylor expanded in x around inf 2.3%
+-commutative2.3%
associate-*r/2.3%
metadata-eval2.3%
rem-square-sqrt2.3%
fabs-sqr2.3%
rem-square-sqrt2.3%
rem-square-sqrt2.3%
fabs-sqr2.3%
rem-square-sqrt2.3%
Simplified2.3%
Final simplification2.3%
(FPCore (x) :precision binary64 (* (sqrt (/ 1.0 PI)) (+ (/ 1.0 x) (/ 1.875 (pow x 7.0)))))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) * ((1.0 / x) + (1.875 / pow(x, 7.0)));
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) * ((1.0 / x) + (1.875 / Math.pow(x, 7.0)));
}
def code(x): return math.sqrt((1.0 / math.pi)) * ((1.0 / x) + (1.875 / math.pow(x, 7.0)))
function code(x) return Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(1.0 / x) + Float64(1.875 / (x ^ 7.0)))) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) * ((1.0 / x) + (1.875 / (x ^ 7.0))); end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(1.0 / x), $MachinePrecision] + N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{\pi}} \cdot \left(\frac{1}{x} + \frac{1.875}{{x}^{7}}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
expm1-log1p-u100.0%
expm1-udef100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Taylor expanded in x around 0 2.3%
Taylor expanded in x around 0 2.3%
+-commutative2.3%
associate-+r+2.3%
Simplified2.3%
Taylor expanded in x around inf 2.3%
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%
expm1-log1p-u100.0%
expm1-udef100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Taylor expanded in x around 0 2.3%
Taylor expanded in x around inf 2.3%
associate-*r*2.3%
*-commutative2.3%
distribute-rgt-out2.3%
associate-*r/2.3%
metadata-eval2.3%
rem-square-sqrt2.3%
fabs-sqr2.3%
rem-square-sqrt2.3%
pow-plus2.3%
metadata-eval2.3%
+-commutative2.3%
Simplified2.3%
Taylor expanded in x around inf 2.3%
associate-*l/2.3%
*-lft-identity2.3%
Simplified2.3%
Final simplification2.3%
herbie shell --seed 2023299
(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)))))))