
(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
(let* ((t_0 (/ 1.0 (fabs x))))
(*
(/ (pow (exp x) x) (sqrt PI))
(fma
1.875
(* (pow t_0 3.0) (pow (/ 1.0 x) 4.0))
(fma
0.75
(+ (+ 1.0 (pow x -5.0)) -1.0)
(fma 0.5 (/ (pow x -2.0) x) t_0))))))
double code(double x) {
double t_0 = 1.0 / fabs(x);
return (pow(exp(x), x) / sqrt(((double) M_PI))) * fma(1.875, (pow(t_0, 3.0) * pow((1.0 / x), 4.0)), fma(0.75, ((1.0 + pow(x, -5.0)) + -1.0), fma(0.5, (pow(x, -2.0) / x), t_0)));
}
function code(x) t_0 = Float64(1.0 / abs(x)) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * fma(1.875, Float64((t_0 ^ 3.0) * (Float64(1.0 / x) ^ 4.0)), fma(0.75, Float64(Float64(1.0 + (x ^ -5.0)) + -1.0), fma(0.5, Float64((x ^ -2.0) / x), t_0)))) end
code[x_] := Block[{t$95$0 = N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision]}, N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(1.875 * N[(N[Power[t$95$0, 3.0], $MachinePrecision] * N[Power[N[(1.0 / x), $MachinePrecision], 4.0], $MachinePrecision]), $MachinePrecision] + N[(0.75 * N[(N[(1.0 + N[Power[x, -5.0], $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision] + N[(0.5 * N[(N[Power[x, -2.0], $MachinePrecision] / x), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{1}{\left|x\right|}\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(1.875, {t_0}^{3} \cdot {\left(\frac{1}{x}\right)}^{4}, \mathsf{fma}\left(0.75, \left(1 + {x}^{-5}\right) + -1, \mathsf{fma}\left(0.5, \frac{{x}^{-2}}{x}, t_0\right)\right)\right)
\end{array}
\end{array}
Initial program 100.0%
Simplified100.0%
expm1-log1p-u100.0%
expm1-udef100.0%
div-inv100.0%
pow-plus100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
div-inv100.0%
pow-plus100.0%
metadata-eval100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
sub-neg100.0%
log1p-udef100.0%
rem-exp-log100.0%
pow1100.0%
pow-div100.0%
metadata-eval100.0%
metadata-eval100.0%
Applied egg-rr100.0%
unpow3100.0%
un-div-inv100.0%
inv-pow100.0%
inv-pow100.0%
pow-prod-up100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(exp (* x x))
(/
(fma
0.75
(+ (+ 1.0 (pow x -5.0)) -1.0)
(fma
1.875
(pow (/ 1.0 (fabs x)) 7.0)
(/ (+ 1.0 (/ 0.5 (* x x))) (fabs x))))
(sqrt PI))))
double code(double x) {
return exp((x * x)) * (fma(0.75, ((1.0 + pow(x, -5.0)) + -1.0), fma(1.875, pow((1.0 / fabs(x)), 7.0), ((1.0 + (0.5 / (x * x))) / fabs(x)))) / sqrt(((double) M_PI)));
}
function code(x) return Float64(exp(Float64(x * x)) * Float64(fma(0.75, Float64(Float64(1.0 + (x ^ -5.0)) + -1.0), fma(1.875, (Float64(1.0 / abs(x)) ^ 7.0), Float64(Float64(1.0 + Float64(0.5 / Float64(x * x))) / abs(x)))) / sqrt(pi))) end
code[x_] := N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * N[(N[(0.75 * N[(N[(1.0 + N[Power[x, -5.0], $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision] + N[(1.875 * N[Power[N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision], 7.0], $MachinePrecision] + N[(N[(1.0 + N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Abs[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x} \cdot \frac{\mathsf{fma}\left(0.75, \left(1 + {x}^{-5}\right) + -1, \mathsf{fma}\left(1.875, {\left(\frac{1}{\left|x\right|}\right)}^{7}, \frac{1 + \frac{0.5}{x \cdot x}}{\left|x\right|}\right)\right)}{\sqrt{\pi}}
\end{array}
Initial program 100.0%
Simplified100.0%
add-sqr-sqrt100.0%
unpow-prod-down100.0%
inv-pow100.0%
sqrt-pow1100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
inv-pow100.0%
sqrt-pow1100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
pow-sqr100.0%
metadata-eval100.0%
Simplified100.0%
expm1-log1p-u100.0%
expm1-udef100.0%
log1p-udef100.0%
add-exp-log100.0%
pow-pow100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(pow (exp x) x)
(*
(fma
0.75
(pow x -5.0)
(+ (/ 1.875 (pow x 7.0)) (+ (/ 1.0 x) (/ 0.5 (pow x 3.0)))))
(pow PI -0.5))))
double code(double x) {
return pow(exp(x), x) * (fma(0.75, pow(x, -5.0), ((1.875 / pow(x, 7.0)) + ((1.0 / x) + (0.5 / pow(x, 3.0))))) * pow(((double) M_PI), -0.5));
}
function code(x) return Float64((exp(x) ^ x) * Float64(fma(0.75, (x ^ -5.0), Float64(Float64(1.875 / (x ^ 7.0)) + Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0))))) * (pi ^ -0.5))) end
code[x_] := N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] * N[(N[(0.75 * N[Power[x, -5.0], $MachinePrecision] + N[(N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision] + N[(N[(1.0 / x), $MachinePrecision] + N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Power[Pi, -0.5], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
{\left(e^{x}\right)}^{x} \cdot \left(\mathsf{fma}\left(0.75, {x}^{-5}, \frac{1.875}{{x}^{7}} + \left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right)\right) \cdot {\pi}^{-0.5}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
div-inv100.0%
Applied egg-rr100.0%
Taylor expanded in x around 0 100.0%
associate-+r+100.0%
+-commutative100.0%
associate-*r/100.0%
metadata-eval100.0%
associate-*r/100.0%
metadata-eval100.0%
+-commutative100.0%
Simplified100.0%
exp-prod99.1%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(exp (* x x))
(*
(sqrt (/ 1.0 PI))
(+
(+ (/ 1.0 x) (/ 0.5 (pow x 3.0)))
(+ (/ 1.875 (pow x 7.0)) (/ 0.75 (pow x 5.0)))))))
double code(double x) {
return exp((x * x)) * (sqrt((1.0 / ((double) M_PI))) * (((1.0 / x) + (0.5 / pow(x, 3.0))) + ((1.875 / pow(x, 7.0)) + (0.75 / pow(x, 5.0)))));
}
public static double code(double x) {
return Math.exp((x * x)) * (Math.sqrt((1.0 / Math.PI)) * (((1.0 / x) + (0.5 / Math.pow(x, 3.0))) + ((1.875 / Math.pow(x, 7.0)) + (0.75 / Math.pow(x, 5.0)))));
}
def code(x): return math.exp((x * x)) * (math.sqrt((1.0 / math.pi)) * (((1.0 / x) + (0.5 / math.pow(x, 3.0))) + ((1.875 / math.pow(x, 7.0)) + (0.75 / math.pow(x, 5.0)))))
function code(x) return Float64(exp(Float64(x * x)) * Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0))) + Float64(Float64(1.875 / (x ^ 7.0)) + Float64(0.75 / (x ^ 5.0)))))) end
function tmp = code(x) tmp = exp((x * x)) * (sqrt((1.0 / pi)) * (((1.0 / x) + (0.5 / (x ^ 3.0))) + ((1.875 / (x ^ 7.0)) + (0.75 / (x ^ 5.0))))); end
code[x_] := N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * 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[(N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision] + N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x} \cdot \left(\sqrt{\frac{1}{\pi}} \cdot \left(\left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right) + \left(\frac{1.875}{{x}^{7}} + \frac{0.75}{{x}^{5}}\right)\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
div-inv100.0%
Applied egg-rr100.0%
Taylor expanded in x around 0 100.0%
associate-+r+100.0%
+-commutative100.0%
associate-*r/100.0%
metadata-eval100.0%
associate-*r/100.0%
metadata-eval100.0%
+-commutative100.0%
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 (* (exp (* x x)) (* (sqrt (/ 1.0 PI)) (+ (/ 1.0 x) (+ (/ 0.5 (pow x 3.0)) (/ 0.75 (pow x 5.0)))))))
double code(double x) {
return exp((x * x)) * (sqrt((1.0 / ((double) M_PI))) * ((1.0 / x) + ((0.5 / pow(x, 3.0)) + (0.75 / pow(x, 5.0)))));
}
public static double code(double x) {
return Math.exp((x * x)) * (Math.sqrt((1.0 / Math.PI)) * ((1.0 / x) + ((0.5 / Math.pow(x, 3.0)) + (0.75 / Math.pow(x, 5.0)))));
}
def code(x): return math.exp((x * x)) * (math.sqrt((1.0 / math.pi)) * ((1.0 / x) + ((0.5 / math.pow(x, 3.0)) + (0.75 / math.pow(x, 5.0)))))
function code(x) return Float64(exp(Float64(x * x)) * Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(1.0 / x) + Float64(Float64(0.5 / (x ^ 3.0)) + Float64(0.75 / (x ^ 5.0)))))) end
function tmp = code(x) tmp = exp((x * x)) * (sqrt((1.0 / pi)) * ((1.0 / x) + ((0.5 / (x ^ 3.0)) + (0.75 / (x ^ 5.0))))); end
code[x_] := N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(1.0 / x), $MachinePrecision] + N[(N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision] + N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x} \cdot \left(\sqrt{\frac{1}{\pi}} \cdot \left(\frac{1}{x} + \left(\frac{0.5}{{x}^{3}} + \frac{0.75}{{x}^{5}}\right)\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
div-inv100.0%
Applied egg-rr100.0%
Taylor expanded in x around 0 100.0%
associate-+r+100.0%
+-commutative100.0%
associate-*r/100.0%
metadata-eval100.0%
associate-*r/100.0%
metadata-eval100.0%
+-commutative100.0%
Simplified100.0%
Taylor expanded in x around inf 99.1%
associate-+r+99.1%
+-commutative99.1%
*-commutative99.1%
associate-*r*99.1%
associate-*r*99.1%
distribute-rgt-out99.1%
distribute-lft-out99.1%
Simplified99.1%
Final simplification99.1%
(FPCore (x) :precision binary64 (* (exp (* x x)) (* (+ (/ 1.0 x) (/ 0.5 (pow x 3.0))) (sqrt (/ 1.0 PI)))))
double code(double x) {
return exp((x * x)) * (((1.0 / x) + (0.5 / pow(x, 3.0))) * sqrt((1.0 / ((double) M_PI))));
}
public static double code(double x) {
return Math.exp((x * x)) * (((1.0 / x) + (0.5 / Math.pow(x, 3.0))) * Math.sqrt((1.0 / Math.PI)));
}
def code(x): return math.exp((x * x)) * (((1.0 / x) + (0.5 / math.pow(x, 3.0))) * math.sqrt((1.0 / math.pi)))
function code(x) return Float64(exp(Float64(x * x)) * Float64(Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0))) * sqrt(Float64(1.0 / pi)))) end
function tmp = code(x) tmp = exp((x * x)) * (((1.0 / x) + (0.5 / (x ^ 3.0))) * sqrt((1.0 / pi))); end
code[x_] := N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * N[(N[(N[(1.0 / x), $MachinePrecision] + N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x} \cdot \left(\left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right) \cdot \sqrt{\frac{1}{\pi}}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
expm1-log1p-u100.0%
expm1-udef5.8%
Applied egg-rr5.8%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Taylor expanded in x around inf 99.1%
associate-*r*99.1%
distribute-rgt-out99.1%
+-commutative99.1%
associate-*r/99.1%
metadata-eval99.1%
Simplified99.1%
Final simplification99.1%
(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%
expm1-log1p-u100.0%
expm1-udef5.8%
Applied egg-rr5.8%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Taylor expanded in x around inf 99.1%
associate-*l/99.1%
*-lft-identity99.1%
Simplified99.1%
expm1-log1p-u99.1%
expm1-udef4.9%
div-inv4.9%
div-inv4.9%
inv-pow4.9%
sqrt-pow14.9%
metadata-eval4.9%
Applied egg-rr4.9%
expm1-def99.1%
expm1-log1p99.1%
Simplified99.1%
Final simplification99.1%
(FPCore (x) :precision binary64 (* (sqrt (/ 1.0 PI)) (+ x (/ 1.0 x))))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) * (x + (1.0 / x));
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) * (x + (1.0 / x));
}
def code(x): return math.sqrt((1.0 / math.pi)) * (x + (1.0 / x))
function code(x) return Float64(sqrt(Float64(1.0 / pi)) * Float64(x + Float64(1.0 / x))) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) * (x + (1.0 / x)); end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(x + N[(1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{\pi}} \cdot \left(x + \frac{1}{x}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
expm1-log1p-u100.0%
expm1-udef5.8%
Applied egg-rr5.8%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Taylor expanded in x around inf 99.1%
associate-*l/99.1%
*-lft-identity99.1%
Simplified99.1%
Taylor expanded in x around 0 5.7%
distribute-rgt-out5.7%
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 100.0%
Simplified100.0%
expm1-log1p-u100.0%
expm1-udef5.8%
Applied egg-rr5.8%
expm1-def100.0%
expm1-log1p100.0%
Simplified100.0%
Taylor expanded in x around inf 99.1%
associate-*l/99.1%
*-lft-identity99.1%
Simplified99.1%
exp-prod99.1%
Applied egg-rr99.1%
Taylor expanded in x around 0 2.4%
associate-*l/2.4%
*-lft-identity2.4%
Simplified2.4%
Final simplification2.4%
herbie shell --seed 2023319
(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)))))))