
(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 11 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 (sqrt (/ 1.0 PI))))
(*
(pow (exp x) x)
(fma
t_0
(+ (/ 1.875 (pow x 7.0)) (+ (/ 0.75 (pow x 5.0)) (/ 1.0 x)))
(* t_0 (/ 0.5 (pow x 3.0)))))))
double code(double x) {
double t_0 = sqrt((1.0 / ((double) M_PI)));
return pow(exp(x), x) * fma(t_0, ((1.875 / pow(x, 7.0)) + ((0.75 / pow(x, 5.0)) + (1.0 / x))), (t_0 * (0.5 / pow(x, 3.0))));
}
function code(x) t_0 = sqrt(Float64(1.0 / pi)) return Float64((exp(x) ^ x) * fma(t_0, Float64(Float64(1.875 / (x ^ 7.0)) + Float64(Float64(0.75 / (x ^ 5.0)) + Float64(1.0 / x))), Float64(t_0 * Float64(0.5 / (x ^ 3.0))))) end
code[x_] := Block[{t$95$0 = N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision]}, N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] * N[(t$95$0 * N[(N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision] + N[(N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision] + N[(1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$0 * N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{\frac{1}{\pi}}\\
{\left(e^{x}\right)}^{x} \cdot \mathsf{fma}\left(t\_0, \frac{1.875}{{x}^{7}} + \left(\frac{0.75}{{x}^{5}} + \frac{1}{x}\right), t\_0 \cdot \frac{0.5}{{x}^{3}}\right)
\end{array}
\end{array}
Initial program 99.9%
Simplified99.9%
Taylor expanded in x around 0 99.9%
associate-*r*99.9%
*-commutative99.9%
distribute-rgt-out99.9%
associate-*r/99.9%
metadata-eval99.9%
unpow299.9%
sqr-abs99.9%
unpow399.9%
Simplified99.9%
exp-prod100.0%
Applied egg-rr100.0%
distribute-lft-in100.0%
pow1/2100.0%
inv-pow100.0%
pow-pow100.0%
metadata-eval100.0%
div-inv100.0%
pow-flip100.0%
metadata-eval100.0%
pow1/2100.0%
inv-pow100.0%
pow-pow100.0%
metadata-eval100.0%
div-inv100.0%
Applied egg-rr100.0%
Taylor expanded in x around 0 100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(*
(pow (exp x) x)
(*
(pow PI -0.5)
(+
(fma 1.875 (pow x -7.0) (fma 0.75 (pow x -5.0) (/ 1.0 x)))
(* 0.5 (pow x -3.0))))))
double code(double x) {
return pow(exp(x), x) * (pow(((double) M_PI), -0.5) * (fma(1.875, pow(x, -7.0), fma(0.75, pow(x, -5.0), (1.0 / x))) + (0.5 * pow(x, -3.0))));
}
function code(x) return Float64((exp(x) ^ x) * Float64((pi ^ -0.5) * Float64(fma(1.875, (x ^ -7.0), fma(0.75, (x ^ -5.0), Float64(1.0 / x))) + Float64(0.5 * (x ^ -3.0))))) end
code[x_] := N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] * N[(N[Power[Pi, -0.5], $MachinePrecision] * N[(N[(1.875 * N[Power[x, -7.0], $MachinePrecision] + N[(0.75 * N[Power[x, -5.0], $MachinePrecision] + N[(1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.5 * N[Power[x, -3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
{\left(e^{x}\right)}^{x} \cdot \left({\pi}^{-0.5} \cdot \left(\mathsf{fma}\left(1.875, {x}^{-7}, \mathsf{fma}\left(0.75, {x}^{-5}, \frac{1}{x}\right)\right) + 0.5 \cdot {x}^{-3}\right)\right)
\end{array}
Initial program 99.9%
Simplified99.9%
Taylor expanded in x around 0 99.9%
associate-*r*99.9%
*-commutative99.9%
distribute-rgt-out99.9%
associate-*r/99.9%
metadata-eval99.9%
unpow299.9%
sqr-abs99.9%
unpow399.9%
Simplified99.9%
exp-prod100.0%
Applied egg-rr100.0%
distribute-lft-in100.0%
pow1/2100.0%
inv-pow100.0%
pow-pow100.0%
metadata-eval100.0%
div-inv100.0%
pow-flip100.0%
metadata-eval100.0%
pow1/2100.0%
inv-pow100.0%
pow-pow100.0%
metadata-eval100.0%
div-inv100.0%
Applied egg-rr100.0%
+-commutative100.0%
distribute-lft-out100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (x)
:precision binary64
(let* ((t_0 (sqrt (/ 1.0 PI))))
(*
(exp (* x x))
(+
(* t_0 (+ (/ 1.875 (pow x 7.0)) (/ 0.75 (pow x 5.0))))
(* t_0 (+ (/ 1.0 x) (/ 0.5 (pow x 3.0))))))))
double code(double x) {
double t_0 = sqrt((1.0 / ((double) M_PI)));
return exp((x * x)) * ((t_0 * ((1.875 / pow(x, 7.0)) + (0.75 / pow(x, 5.0)))) + (t_0 * ((1.0 / x) + (0.5 / pow(x, 3.0)))));
}
public static double code(double x) {
double t_0 = Math.sqrt((1.0 / Math.PI));
return Math.exp((x * x)) * ((t_0 * ((1.875 / Math.pow(x, 7.0)) + (0.75 / Math.pow(x, 5.0)))) + (t_0 * ((1.0 / x) + (0.5 / Math.pow(x, 3.0)))));
}
def code(x): t_0 = math.sqrt((1.0 / math.pi)) return math.exp((x * x)) * ((t_0 * ((1.875 / math.pow(x, 7.0)) + (0.75 / math.pow(x, 5.0)))) + (t_0 * ((1.0 / x) + (0.5 / math.pow(x, 3.0)))))
function code(x) t_0 = sqrt(Float64(1.0 / pi)) return Float64(exp(Float64(x * x)) * Float64(Float64(t_0 * Float64(Float64(1.875 / (x ^ 7.0)) + Float64(0.75 / (x ^ 5.0)))) + Float64(t_0 * Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0)))))) end
function tmp = code(x) t_0 = sqrt((1.0 / pi)); tmp = exp((x * x)) * ((t_0 * ((1.875 / (x ^ 7.0)) + (0.75 / (x ^ 5.0)))) + (t_0 * ((1.0 / x) + (0.5 / (x ^ 3.0))))); end
code[x_] := Block[{t$95$0 = N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision]}, N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * N[(N[(t$95$0 * N[(N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision] + N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$0 * N[(N[(1.0 / x), $MachinePrecision] + N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{\frac{1}{\pi}}\\
e^{x \cdot x} \cdot \left(t\_0 \cdot \left(\frac{1.875}{{x}^{7}} + \frac{0.75}{{x}^{5}}\right) + t\_0 \cdot \left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right)\right)
\end{array}
\end{array}
Initial program 99.9%
Simplified99.9%
expm1-log1p-u99.9%
expm1-udef3.8%
Applied egg-rr3.8%
expm1-def99.9%
expm1-log1p99.9%
Simplified99.9%
Taylor expanded in x around 0 99.9%
+-commutative99.9%
associate-+r+99.9%
associate-+l+99.9%
Simplified99.9%
Final simplification99.9%
(FPCore (x)
:precision binary64
(let* ((t_0 (sqrt (/ 1.0 PI))))
(*
(exp (* x x))
(+ (/ t_0 x) (* t_0 (+ (/ 0.75 (pow x 5.0)) (/ 0.5 (pow x 3.0))))))))
double code(double x) {
double t_0 = sqrt((1.0 / ((double) M_PI)));
return exp((x * x)) * ((t_0 / x) + (t_0 * ((0.75 / pow(x, 5.0)) + (0.5 / pow(x, 3.0)))));
}
public static double code(double x) {
double t_0 = Math.sqrt((1.0 / Math.PI));
return Math.exp((x * x)) * ((t_0 / x) + (t_0 * ((0.75 / Math.pow(x, 5.0)) + (0.5 / Math.pow(x, 3.0)))));
}
def code(x): t_0 = math.sqrt((1.0 / math.pi)) return math.exp((x * x)) * ((t_0 / x) + (t_0 * ((0.75 / math.pow(x, 5.0)) + (0.5 / math.pow(x, 3.0)))))
function code(x) t_0 = sqrt(Float64(1.0 / pi)) return Float64(exp(Float64(x * x)) * Float64(Float64(t_0 / x) + Float64(t_0 * Float64(Float64(0.75 / (x ^ 5.0)) + Float64(0.5 / (x ^ 3.0)))))) end
function tmp = code(x) t_0 = sqrt((1.0 / pi)); tmp = exp((x * x)) * ((t_0 / x) + (t_0 * ((0.75 / (x ^ 5.0)) + (0.5 / (x ^ 3.0))))); end
code[x_] := Block[{t$95$0 = N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision]}, N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * N[(N[(t$95$0 / x), $MachinePrecision] + N[(t$95$0 * N[(N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision] + N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{\frac{1}{\pi}}\\
e^{x \cdot x} \cdot \left(\frac{t\_0}{x} + t\_0 \cdot \left(\frac{0.75}{{x}^{5}} + \frac{0.5}{{x}^{3}}\right)\right)
\end{array}
\end{array}
Initial program 99.9%
Simplified99.9%
expm1-log1p-u99.9%
expm1-udef3.8%
Applied egg-rr3.8%
expm1-def99.9%
expm1-log1p99.9%
Simplified99.9%
Taylor expanded in x around inf 99.3%
associate-+r+99.3%
+-commutative99.3%
associate-*l/99.3%
*-lft-identity99.3%
associate-*r*99.3%
associate-*r*99.3%
distribute-rgt-out99.3%
associate-*r/99.3%
metadata-eval99.3%
associate-*r/99.3%
metadata-eval99.3%
Simplified99.3%
Final simplification99.3%
(FPCore (x) :precision binary64 (* (* (sqrt (/ 1.0 PI)) (+ (/ 1.0 x) (/ 0.5 (pow x 3.0)))) (pow (sqrt (exp x)) (* x 2.0))))
double code(double x) {
return (sqrt((1.0 / ((double) M_PI))) * ((1.0 / x) + (0.5 / pow(x, 3.0)))) * pow(sqrt(exp(x)), (x * 2.0));
}
public static double code(double x) {
return (Math.sqrt((1.0 / Math.PI)) * ((1.0 / x) + (0.5 / Math.pow(x, 3.0)))) * Math.pow(Math.sqrt(Math.exp(x)), (x * 2.0));
}
def code(x): return (math.sqrt((1.0 / math.pi)) * ((1.0 / x) + (0.5 / math.pow(x, 3.0)))) * math.pow(math.sqrt(math.exp(x)), (x * 2.0))
function code(x) return Float64(Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0)))) * (sqrt(exp(x)) ^ Float64(x * 2.0))) end
function tmp = code(x) tmp = (sqrt((1.0 / pi)) * ((1.0 / x) + (0.5 / (x ^ 3.0)))) * (sqrt(exp(x)) ^ (x * 2.0)); end
code[x_] := N[(N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(1.0 / x), $MachinePrecision] + N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Power[N[Sqrt[N[Exp[x], $MachinePrecision]], $MachinePrecision], N[(x * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\sqrt{\frac{1}{\pi}} \cdot \left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right)\right) \cdot {\left(\sqrt{e^{x}}\right)}^{\left(x \cdot 2\right)}
\end{array}
Initial program 99.9%
Simplified99.9%
expm1-log1p-u99.9%
expm1-udef3.8%
Applied egg-rr3.8%
expm1-def99.9%
expm1-log1p99.9%
Simplified99.9%
Taylor expanded in x around inf 99.2%
associate-*r*99.2%
distribute-rgt-out99.2%
associate-*r/99.2%
metadata-eval99.2%
Simplified99.2%
exp-prod100.0%
Applied egg-rr99.2%
add-sqr-sqrt99.2%
unpow-prod-down99.2%
Applied egg-rr99.2%
pow-sqr99.2%
*-commutative99.2%
Simplified99.2%
Final simplification99.2%
(FPCore (x) :precision binary64 (* (exp (* x x)) (+ (/ (pow PI -0.5) x) (/ 0.5 (* (pow x 3.0) (sqrt PI))))))
double code(double x) {
return exp((x * x)) * ((pow(((double) M_PI), -0.5) / x) + (0.5 / (pow(x, 3.0) * sqrt(((double) M_PI)))));
}
public static double code(double x) {
return Math.exp((x * x)) * ((Math.pow(Math.PI, -0.5) / x) + (0.5 / (Math.pow(x, 3.0) * Math.sqrt(Math.PI))));
}
def code(x): return math.exp((x * x)) * ((math.pow(math.pi, -0.5) / x) + (0.5 / (math.pow(x, 3.0) * math.sqrt(math.pi))))
function code(x) return Float64(exp(Float64(x * x)) * Float64(Float64((pi ^ -0.5) / x) + Float64(0.5 / Float64((x ^ 3.0) * sqrt(pi))))) end
function tmp = code(x) tmp = exp((x * x)) * (((pi ^ -0.5) / x) + (0.5 / ((x ^ 3.0) * sqrt(pi)))); end
code[x_] := N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] * N[(N[(N[Power[Pi, -0.5], $MachinePrecision] / x), $MachinePrecision] + N[(0.5 / N[(N[Power[x, 3.0], $MachinePrecision] * N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x} \cdot \left(\frac{{\pi}^{-0.5}}{x} + \frac{0.5}{{x}^{3} \cdot \sqrt{\pi}}\right)
\end{array}
Initial program 99.9%
Simplified99.9%
expm1-log1p-u99.9%
expm1-udef3.8%
Applied egg-rr3.8%
expm1-def99.9%
expm1-log1p99.9%
Simplified99.9%
Taylor expanded in x around inf 99.2%
associate-*r*99.2%
distribute-rgt-out99.2%
associate-*r/99.2%
metadata-eval99.2%
Simplified99.2%
+-commutative99.2%
distribute-lft-in99.2%
div-inv99.2%
inv-pow99.2%
sqrt-pow199.2%
metadata-eval99.2%
sqrt-div99.2%
metadata-eval99.2%
frac-times99.2%
metadata-eval99.2%
Applied egg-rr99.2%
*-commutative99.2%
Simplified99.2%
Final simplification99.2%
(FPCore (x) :precision binary64 (* (pow (exp x) x) (* (sqrt (/ 1.0 PI)) (+ (/ 1.0 x) (/ 0.5 (pow x 3.0))))))
double code(double x) {
return pow(exp(x), x) * (sqrt((1.0 / ((double) M_PI))) * ((1.0 / x) + (0.5 / pow(x, 3.0))));
}
public static double code(double x) {
return Math.pow(Math.exp(x), x) * (Math.sqrt((1.0 / Math.PI)) * ((1.0 / x) + (0.5 / Math.pow(x, 3.0))));
}
def code(x): return math.pow(math.exp(x), x) * (math.sqrt((1.0 / math.pi)) * ((1.0 / x) + (0.5 / math.pow(x, 3.0))))
function code(x) return Float64((exp(x) ^ x) * Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0))))) end
function tmp = code(x) tmp = (exp(x) ^ x) * (sqrt((1.0 / pi)) * ((1.0 / x) + (0.5 / (x ^ 3.0)))); end
code[x_] := N[(N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] * N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[(1.0 / x), $MachinePrecision] + N[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
{\left(e^{x}\right)}^{x} \cdot \left(\sqrt{\frac{1}{\pi}} \cdot \left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right)\right)
\end{array}
Initial program 99.9%
Simplified99.9%
expm1-log1p-u99.9%
expm1-udef3.8%
Applied egg-rr3.8%
expm1-def99.9%
expm1-log1p99.9%
Simplified99.9%
Taylor expanded in x around inf 99.2%
associate-*r*99.2%
distribute-rgt-out99.2%
associate-*r/99.2%
metadata-eval99.2%
Simplified99.2%
exp-prod100.0%
Applied egg-rr99.2%
Final simplification99.2%
(FPCore (x) :precision binary64 (* (exp (* x x)) (* (sqrt (/ 1.0 PI)) (+ (/ 1.0 x) (/ 0.5 (pow x 3.0))))))
double code(double x) {
return exp((x * x)) * (sqrt((1.0 / ((double) M_PI))) * ((1.0 / x) + (0.5 / pow(x, 3.0))));
}
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))));
}
def code(x): return math.exp((x * x)) * (math.sqrt((1.0 / math.pi)) * ((1.0 / x) + (0.5 / math.pow(x, 3.0))))
function code(x) return Float64(exp(Float64(x * x)) * Float64(sqrt(Float64(1.0 / pi)) * Float64(Float64(1.0 / x) + Float64(0.5 / (x ^ 3.0))))) end
function tmp = code(x) tmp = exp((x * x)) * (sqrt((1.0 / pi)) * ((1.0 / x) + (0.5 / (x ^ 3.0)))); 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[(0.5 / N[Power[x, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
e^{x \cdot x} \cdot \left(\sqrt{\frac{1}{\pi}} \cdot \left(\frac{1}{x} + \frac{0.5}{{x}^{3}}\right)\right)
\end{array}
Initial program 99.9%
Simplified99.9%
expm1-log1p-u99.9%
expm1-udef3.8%
Applied egg-rr3.8%
expm1-def99.9%
expm1-log1p99.9%
Simplified99.9%
Taylor expanded in x around inf 99.2%
associate-*r*99.2%
distribute-rgt-out99.2%
associate-*r/99.2%
metadata-eval99.2%
Simplified99.2%
Final simplification99.2%
(FPCore (x) :precision binary64 (* (pow (exp x) x) (/ (pow PI -0.5) x)))
double code(double x) {
return pow(exp(x), x) * (pow(((double) M_PI), -0.5) / x);
}
public static double code(double x) {
return Math.pow(Math.exp(x), x) * (Math.pow(Math.PI, -0.5) / x);
}
def code(x): return math.pow(math.exp(x), x) * (math.pow(math.pi, -0.5) / x)
function code(x) return Float64((exp(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[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision] * N[(N[Power[Pi, -0.5], $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
{\left(e^{x}\right)}^{x} \cdot \frac{{\pi}^{-0.5}}{x}
\end{array}
Initial program 99.9%
Simplified99.9%
expm1-log1p-u99.9%
expm1-udef3.8%
Applied egg-rr3.8%
expm1-def99.9%
expm1-log1p99.9%
Simplified99.9%
Taylor expanded in x around inf 99.1%
associate-*l/99.1%
*-lft-identity99.1%
Simplified99.1%
exp-prod100.0%
Applied egg-rr99.1%
*-un-lft-identity2.3%
associate-*l/2.3%
expm1-log1p-u2.3%
expm1-udef1.7%
associate-*l/1.7%
*-un-lft-identity1.7%
inv-pow1.7%
sqrt-pow11.7%
metadata-eval1.7%
Applied egg-rr3.0%
expm1-def2.3%
expm1-log1p2.3%
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 99.9%
Simplified99.9%
expm1-log1p-u99.9%
expm1-udef3.8%
Applied egg-rr3.8%
expm1-def99.9%
expm1-log1p99.9%
Simplified99.9%
Taylor expanded in x around inf 99.1%
associate-*l/99.1%
*-lft-identity99.1%
Simplified99.1%
*-un-lft-identity2.3%
associate-*l/2.3%
expm1-log1p-u2.3%
expm1-udef1.7%
associate-*l/1.7%
*-un-lft-identity1.7%
inv-pow1.7%
sqrt-pow11.7%
metadata-eval1.7%
Applied egg-rr3.0%
expm1-def2.3%
expm1-log1p2.3%
Simplified99.1%
Final simplification99.1%
(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 99.9%
Simplified99.9%
expm1-log1p-u99.9%
expm1-udef3.8%
Applied egg-rr3.8%
expm1-def99.9%
expm1-log1p99.9%
Simplified99.9%
Taylor expanded in x around inf 99.1%
associate-*l/99.1%
*-lft-identity99.1%
Simplified99.1%
Taylor expanded in x around 0 2.3%
*-un-lft-identity2.3%
associate-*l/2.3%
expm1-log1p-u2.3%
expm1-udef1.7%
associate-*l/1.7%
*-un-lft-identity1.7%
inv-pow1.7%
sqrt-pow11.7%
metadata-eval1.7%
Applied egg-rr1.7%
expm1-def2.3%
expm1-log1p2.3%
Simplified2.3%
Final simplification2.3%
herbie shell --seed 2024026
(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)))))))