
(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 15 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) (* 0.5 (log PI)))) (+ (* 0.5 (pow x -3.0)) (/ (+ 1.0 (fma 0.75 (pow x -4.0) (* 1.875 (pow x -6.0)))) x))))
double code(double x) {
return exp(((x * x) - (0.5 * log(((double) M_PI))))) * ((0.5 * pow(x, -3.0)) + ((1.0 + fma(0.75, pow(x, -4.0), (1.875 * pow(x, -6.0)))) / x));
}
function code(x) return Float64(exp(Float64(Float64(x * x) - Float64(0.5 * log(pi)))) * Float64(Float64(0.5 * (x ^ -3.0)) + Float64(Float64(1.0 + fma(0.75, (x ^ -4.0), Float64(1.875 * (x ^ -6.0)))) / x))) end
code[x_] := N[(N[Exp[N[(N[(x * x), $MachinePrecision] - N[(0.5 * N[Log[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(N[(0.5 * N[Power[x, -3.0], $MachinePrecision]), $MachinePrecision] + N[(N[(1.0 + N[(0.75 * N[Power[x, -4.0], $MachinePrecision] + N[(1.875 * N[Power[x, -6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x - 0.5 \cdot \log \pi} \cdot \left(0.5 \cdot {x}^{-3} + \frac{1 + \mathsf{fma}\left(0.75, {x}^{-4}, 1.875 \cdot {x}^{-6}\right)}{x}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
add-exp-log100.0%
log-div100.0%
pow-exp100.0%
add-log-exp100.0%
pow2100.0%
Applied egg-rr100.0%
unpow2100.0%
Applied egg-rr100.0%
pow1/2100.0%
log-pow100.0%
Applied egg-rr100.0%
(FPCore (x)
:precision binary64
(*
(/ (pow (exp x) x) (sqrt PI))
(/
(+
(+ (/ 0.5 (pow x 2.0)) (/ 1.875 (pow x 6.0)))
(+ 1.0 (/ 0.75 (pow x 4.0))))
x)))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * ((((0.5 / pow(x, 2.0)) + (1.875 / pow(x, 6.0))) + (1.0 + (0.75 / pow(x, 4.0)))) / x);
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / Math.sqrt(Math.PI)) * ((((0.5 / Math.pow(x, 2.0)) + (1.875 / Math.pow(x, 6.0))) + (1.0 + (0.75 / Math.pow(x, 4.0)))) / x);
}
def code(x): return (math.pow(math.exp(x), x) / math.sqrt(math.pi)) * ((((0.5 / math.pow(x, 2.0)) + (1.875 / math.pow(x, 6.0))) + (1.0 + (0.75 / math.pow(x, 4.0)))) / x)
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * Float64(Float64(Float64(Float64(0.5 / (x ^ 2.0)) + Float64(1.875 / (x ^ 6.0))) + Float64(1.0 + Float64(0.75 / (x ^ 4.0)))) / x)) end
function tmp = code(x) tmp = ((exp(x) ^ x) / sqrt(pi)) * ((((0.5 / (x ^ 2.0)) + (1.875 / (x ^ 6.0))) + (1.0 + (0.75 / (x ^ 4.0)))) / x); end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(1.0 + N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \frac{\left(\frac{0.5}{{x}^{2}} + \frac{1.875}{{x}^{6}}\right) + \left(1 + \frac{0.75}{{x}^{4}}\right)}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 100.0%
associate-+r+100.0%
+-commutative100.0%
associate-*r/100.0%
metadata-eval100.0%
associate-*r/100.0%
metadata-eval100.0%
Simplified100.0%
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (+ (+ (* 0.75 (pow x -5.0)) (* 1.875 (pow x -7.0))) (/ (fma 0.5 (pow x -2.0) 1.0) x))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * (((0.75 * pow(x, -5.0)) + (1.875 * pow(x, -7.0))) + (fma(0.5, pow(x, -2.0), 1.0) / x));
}
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * Float64(Float64(Float64(0.75 * (x ^ -5.0)) + Float64(1.875 * (x ^ -7.0))) + Float64(fma(0.5, (x ^ -2.0), 1.0) / x))) end
code[x_] := N[(N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(0.75 * N[Power[x, -5.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 * N[Power[x, -7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(0.5 * N[Power[x, -2.0], $MachinePrecision] + 1.0), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \left(\left(0.75 \cdot {x}^{-5} + 1.875 \cdot {x}^{-7}\right) + \frac{\mathsf{fma}\left(0.5, {x}^{-2}, 1\right)}{x}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
fma-undefine100.0%
associate-+r+100.0%
Applied egg-rr100.0%
(FPCore (x) :precision binary64 (* (exp (- (pow x 2.0) (log (sqrt PI)))) (/ (+ (/ 0.5 (pow x 2.0)) (+ 1.0 (/ 0.75 (pow x 4.0)))) x)))
double code(double x) {
return exp((pow(x, 2.0) - log(sqrt(((double) M_PI))))) * (((0.5 / pow(x, 2.0)) + (1.0 + (0.75 / pow(x, 4.0)))) / x);
}
public static double code(double x) {
return Math.exp((Math.pow(x, 2.0) - Math.log(Math.sqrt(Math.PI)))) * (((0.5 / Math.pow(x, 2.0)) + (1.0 + (0.75 / Math.pow(x, 4.0)))) / x);
}
def code(x): return math.exp((math.pow(x, 2.0) - math.log(math.sqrt(math.pi)))) * (((0.5 / math.pow(x, 2.0)) + (1.0 + (0.75 / math.pow(x, 4.0)))) / x)
function code(x) return Float64(exp(Float64((x ^ 2.0) - log(sqrt(pi)))) * Float64(Float64(Float64(0.5 / (x ^ 2.0)) + Float64(1.0 + Float64(0.75 / (x ^ 4.0)))) / x)) end
function tmp = code(x) tmp = exp(((x ^ 2.0) - log(sqrt(pi)))) * (((0.5 / (x ^ 2.0)) + (1.0 + (0.75 / (x ^ 4.0)))) / x); end
code[x_] := N[(N[Exp[N[(N[Power[x, 2.0], $MachinePrecision] - N[Log[N[Sqrt[Pi], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(N[(N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision] + N[(1.0 + N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{{x}^{2} - \log \left(\sqrt{\pi}\right)} \cdot \frac{\frac{0.5}{{x}^{2}} + \left(1 + \frac{0.75}{{x}^{4}}\right)}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
add-exp-log100.0%
log-div100.0%
pow-exp100.0%
add-log-exp100.0%
pow2100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.8%
associate-+r+99.8%
+-commutative99.8%
associate-*r/99.8%
metadata-eval99.8%
Simplified99.8%
(FPCore (x) :precision binary64 (* (exp (- (* x x) (log (sqrt PI)))) (+ (* 0.5 (pow x -3.0)) (/ (+ 1.0 (/ 0.75 (pow x 4.0))) x))))
double code(double x) {
return exp(((x * x) - log(sqrt(((double) M_PI))))) * ((0.5 * pow(x, -3.0)) + ((1.0 + (0.75 / pow(x, 4.0))) / x));
}
public static double code(double x) {
return Math.exp(((x * x) - Math.log(Math.sqrt(Math.PI)))) * ((0.5 * Math.pow(x, -3.0)) + ((1.0 + (0.75 / Math.pow(x, 4.0))) / x));
}
def code(x): return math.exp(((x * x) - math.log(math.sqrt(math.pi)))) * ((0.5 * math.pow(x, -3.0)) + ((1.0 + (0.75 / math.pow(x, 4.0))) / x))
function code(x) return Float64(exp(Float64(Float64(x * x) - log(sqrt(pi)))) * Float64(Float64(0.5 * (x ^ -3.0)) + Float64(Float64(1.0 + Float64(0.75 / (x ^ 4.0))) / x))) end
function tmp = code(x) tmp = exp(((x * x) - log(sqrt(pi)))) * ((0.5 * (x ^ -3.0)) + ((1.0 + (0.75 / (x ^ 4.0))) / x)); end
code[x_] := N[(N[Exp[N[(N[(x * x), $MachinePrecision] - N[Log[N[Sqrt[Pi], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(N[(0.5 * N[Power[x, -3.0], $MachinePrecision]), $MachinePrecision] + N[(N[(1.0 + N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x - \log \left(\sqrt{\pi}\right)} \cdot \left(0.5 \cdot {x}^{-3} + \frac{1 + \frac{0.75}{{x}^{4}}}{x}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
add-exp-log100.0%
log-div100.0%
pow-exp100.0%
add-log-exp100.0%
pow2100.0%
Applied egg-rr100.0%
unpow2100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.8%
(FPCore (x) :precision binary64 (* (/ (pow (exp x) x) (sqrt PI)) (/ (+ (/ 0.5 (pow x 2.0)) (+ 1.0 (/ 0.75 (pow x 4.0)))) x)))
double code(double x) {
return (pow(exp(x), x) / sqrt(((double) M_PI))) * (((0.5 / pow(x, 2.0)) + (1.0 + (0.75 / pow(x, 4.0)))) / x);
}
public static double code(double x) {
return (Math.pow(Math.exp(x), x) / Math.sqrt(Math.PI)) * (((0.5 / Math.pow(x, 2.0)) + (1.0 + (0.75 / Math.pow(x, 4.0)))) / x);
}
def code(x): return (math.pow(math.exp(x), x) / math.sqrt(math.pi)) * (((0.5 / math.pow(x, 2.0)) + (1.0 + (0.75 / math.pow(x, 4.0)))) / x)
function code(x) return Float64(Float64((exp(x) ^ x) / sqrt(pi)) * Float64(Float64(Float64(0.5 / (x ^ 2.0)) + Float64(1.0 + Float64(0.75 / (x ^ 4.0)))) / x)) end
function tmp = code(x) tmp = ((exp(x) ^ x) / sqrt(pi)) * (((0.5 / (x ^ 2.0)) + (1.0 + (0.75 / (x ^ 4.0)))) / x); end
code[x_] := N[(N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision] + N[(1.0 + N[(0.75 / N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(e^{x}\right)}^{x}}{\sqrt{\pi}} \cdot \frac{\frac{0.5}{{x}^{2}} + \left(1 + \frac{0.75}{{x}^{4}}\right)}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.8%
associate-+r+99.8%
+-commutative99.8%
associate-*r/99.8%
metadata-eval99.8%
Simplified99.8%
(FPCore (x) :precision binary64 (/ (exp (pow x 2.0)) (* (sqrt PI) (/ x (fma 0.5 (pow x -2.0) 1.0)))))
double code(double x) {
return exp(pow(x, 2.0)) / (sqrt(((double) M_PI)) * (x / fma(0.5, pow(x, -2.0), 1.0)));
}
function code(x) return Float64(exp((x ^ 2.0)) / Float64(sqrt(pi) * Float64(x / fma(0.5, (x ^ -2.0), 1.0)))) end
code[x_] := N[(N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision] / N[(N[Sqrt[Pi], $MachinePrecision] * N[(x / N[(0.5 * N[Power[x, -2.0], $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{{x}^{2}}}{\sqrt{\pi} \cdot \frac{x}{\mathsf{fma}\left(0.5, {x}^{-2}, 1\right)}}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.8%
associate-*r/99.8%
metadata-eval99.8%
Simplified99.8%
*-commutative99.8%
clear-num99.8%
frac-times99.8%
*-un-lft-identity99.8%
pow-exp99.8%
unpow299.8%
+-commutative99.8%
div-inv99.8%
fma-define99.8%
pow-flip99.8%
metadata-eval99.8%
Applied egg-rr99.8%
Final simplification99.8%
(FPCore (x) :precision binary64 (* (/ (exp (pow x 2.0)) (sqrt PI)) (/ (+ 1.0 (/ 0.5 (* x x))) x)))
double code(double x) {
return (exp(pow(x, 2.0)) / sqrt(((double) M_PI))) * ((1.0 + (0.5 / (x * x))) / x);
}
public static double code(double x) {
return (Math.exp(Math.pow(x, 2.0)) / Math.sqrt(Math.PI)) * ((1.0 + (0.5 / (x * x))) / x);
}
def code(x): return (math.exp(math.pow(x, 2.0)) / math.sqrt(math.pi)) * ((1.0 + (0.5 / (x * x))) / x)
function code(x) return Float64(Float64(exp((x ^ 2.0)) / sqrt(pi)) * Float64(Float64(1.0 + Float64(0.5 / Float64(x * x))) / x)) end
function tmp = code(x) tmp = (exp((x ^ 2.0)) / sqrt(pi)) * ((1.0 + (0.5 / (x * x))) / x); end
code[x_] := N[(N[(N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 + N[(0.5 / N[(x * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{{x}^{2}}}{\sqrt{\pi}} \cdot \frac{1 + \frac{0.5}{x \cdot x}}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.8%
associate-*r/99.8%
metadata-eval99.8%
Simplified99.8%
*-un-lft-identity99.8%
pow-exp99.8%
pow299.8%
Applied egg-rr99.8%
*-lft-identity99.8%
Simplified99.8%
unpow2100.0%
Applied egg-rr99.8%
(FPCore (x) :precision binary64 (/ (/ (exp (pow x 2.0)) (sqrt PI)) x))
double code(double x) {
return (exp(pow(x, 2.0)) / sqrt(((double) M_PI))) / x;
}
public static double code(double x) {
return (Math.exp(Math.pow(x, 2.0)) / Math.sqrt(Math.PI)) / x;
}
def code(x): return (math.exp(math.pow(x, 2.0)) / math.sqrt(math.pi)) / x
function code(x) return Float64(Float64(exp((x ^ 2.0)) / sqrt(pi)) / x) end
function tmp = code(x) tmp = (exp((x ^ 2.0)) / sqrt(pi)) / x; end
code[x_] := N[(N[(N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{e^{{x}^{2}}}{\sqrt{\pi}}}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
un-div-inv99.7%
pow-exp99.7%
unpow299.7%
Applied egg-rr99.7%
(FPCore (x) :precision binary64 (* (/ (pow (+ 1.0 (* x (+ 1.0 (* x (+ 0.5 (* x 0.16666666666666666)))))) x) (sqrt PI)) (/ 1.0 x)))
double code(double x) {
return (pow((1.0 + (x * (1.0 + (x * (0.5 + (x * 0.16666666666666666)))))), x) / sqrt(((double) M_PI))) * (1.0 / x);
}
public static double code(double x) {
return (Math.pow((1.0 + (x * (1.0 + (x * (0.5 + (x * 0.16666666666666666)))))), x) / Math.sqrt(Math.PI)) * (1.0 / x);
}
def code(x): return (math.pow((1.0 + (x * (1.0 + (x * (0.5 + (x * 0.16666666666666666)))))), x) / math.sqrt(math.pi)) * (1.0 / x)
function code(x) return Float64(Float64((Float64(1.0 + Float64(x * Float64(1.0 + Float64(x * Float64(0.5 + Float64(x * 0.16666666666666666)))))) ^ x) / sqrt(pi)) * Float64(1.0 / x)) end
function tmp = code(x) tmp = (((1.0 + (x * (1.0 + (x * (0.5 + (x * 0.16666666666666666)))))) ^ x) / sqrt(pi)) * (1.0 / x); end
code[x_] := N[(N[(N[Power[N[(1.0 + N[(x * N[(1.0 + N[(x * N[(0.5 + N[(x * 0.16666666666666666), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(1.0 / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(1 + x \cdot \left(1 + x \cdot \left(0.5 + x \cdot 0.16666666666666666\right)\right)\right)}^{x}}{\sqrt{\pi}} \cdot \frac{1}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
Taylor expanded in x around 0 99.6%
*-commutative99.6%
Simplified99.6%
(FPCore (x) :precision binary64 (* (/ 1.0 x) (/ (pow (+ 1.0 (* x (+ 1.0 (* x 0.5)))) x) (sqrt PI))))
double code(double x) {
return (1.0 / x) * (pow((1.0 + (x * (1.0 + (x * 0.5)))), x) / sqrt(((double) M_PI)));
}
public static double code(double x) {
return (1.0 / x) * (Math.pow((1.0 + (x * (1.0 + (x * 0.5)))), x) / Math.sqrt(Math.PI));
}
def code(x): return (1.0 / x) * (math.pow((1.0 + (x * (1.0 + (x * 0.5)))), x) / math.sqrt(math.pi))
function code(x) return Float64(Float64(1.0 / x) * Float64((Float64(1.0 + Float64(x * Float64(1.0 + Float64(x * 0.5)))) ^ x) / sqrt(pi))) end
function tmp = code(x) tmp = (1.0 / x) * (((1.0 + (x * (1.0 + (x * 0.5)))) ^ x) / sqrt(pi)); end
code[x_] := N[(N[(1.0 / x), $MachinePrecision] * N[(N[Power[N[(1.0 + N[(x * N[(1.0 + N[(x * 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{x} \cdot \frac{{\left(1 + x \cdot \left(1 + x \cdot 0.5\right)\right)}^{x}}{\sqrt{\pi}}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
Taylor expanded in x around 0 99.6%
*-commutative99.6%
Simplified99.6%
Final simplification99.6%
(FPCore (x) :precision binary64 (* (/ 1.0 x) (/ (pow (+ x 1.0) x) (sqrt PI))))
double code(double x) {
return (1.0 / x) * (pow((x + 1.0), x) / sqrt(((double) M_PI)));
}
public static double code(double x) {
return (1.0 / x) * (Math.pow((x + 1.0), x) / Math.sqrt(Math.PI));
}
def code(x): return (1.0 / x) * (math.pow((x + 1.0), x) / math.sqrt(math.pi))
function code(x) return Float64(Float64(1.0 / x) * Float64((Float64(x + 1.0) ^ x) / sqrt(pi))) end
function tmp = code(x) tmp = (1.0 / x) * (((x + 1.0) ^ x) / sqrt(pi)); end
code[x_] := N[(N[(1.0 / x), $MachinePrecision] * N[(N[Power[N[(x + 1.0), $MachinePrecision], x], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{x} \cdot \frac{{\left(x + 1\right)}^{x}}{\sqrt{\pi}}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
Taylor expanded in x around 0 99.3%
Final simplification99.3%
(FPCore (x) :precision binary64 (/ (/ (fma x x 1.0) x) (sqrt PI)))
double code(double x) {
return (fma(x, x, 1.0) / x) / sqrt(((double) M_PI));
}
function code(x) return Float64(Float64(fma(x, x, 1.0) / x) / sqrt(pi)) end
code[x_] := N[(N[(N[(x * x + 1.0), $MachinePrecision] / x), $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{\frac{\mathsf{fma}\left(x, x, 1\right)}{x}}{\sqrt{\pi}}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
Taylor expanded in x around 0 57.2%
+-commutative57.2%
unpow257.2%
fma-define57.2%
Simplified57.2%
associate-*l/57.2%
un-div-inv57.2%
Applied egg-rr57.2%
(FPCore (x) :precision binary64 (* x (sqrt (/ 1.0 PI))))
double code(double x) {
return x * sqrt((1.0 / ((double) M_PI)));
}
public static double code(double x) {
return x * Math.sqrt((1.0 / Math.PI));
}
def code(x): return x * math.sqrt((1.0 / math.pi))
function code(x) return Float64(x * sqrt(Float64(1.0 / pi))) end
function tmp = code(x) tmp = x * sqrt((1.0 / pi)); end
code[x_] := N[(x * N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
x \cdot \sqrt{\frac{1}{\pi}}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
Taylor expanded in x around 0 57.2%
+-commutative57.2%
unpow257.2%
fma-define57.2%
Simplified57.2%
Taylor expanded in x around inf 5.5%
(FPCore (x) :precision binary64 (/ (pow PI -0.5) x))
double code(double x) {
return pow(((double) M_PI), -0.5) / x;
}
public static double code(double x) {
return Math.pow(Math.PI, -0.5) / x;
}
def code(x): return math.pow(math.pi, -0.5) / x
function code(x) return Float64((pi ^ -0.5) / x) end
function tmp = code(x) tmp = (pi ^ -0.5) / x; end
code[x_] := N[(N[Power[Pi, -0.5], $MachinePrecision] / x), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\pi}^{-0.5}}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
fma-undefine100.0%
pow-flip100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
associate-*l/100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
Taylor expanded in x around 0 2.2%
associate-*l/2.2%
*-lft-identity2.2%
unpow1/22.2%
rem-exp-log2.2%
exp-neg2.2%
exp-prod2.2%
distribute-lft-neg-in2.2%
distribute-rgt-neg-in2.2%
metadata-eval2.2%
exp-to-pow2.2%
Simplified2.2%
herbie shell --seed 2024137
(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)))))))