
(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 5 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (x)
:precision binary64
(let* ((t_0 (/ 1.0 (fabs x)))
(t_1 (* (* t_0 t_0) t_0))
(t_2 (* (* t_1 t_0) t_0)))
(*
(* (/ 1.0 (sqrt PI)) (exp (* (fabs x) (fabs x))))
(+
(+ (+ t_0 (* (/ 1.0 2.0) t_1)) (* (/ 3.0 4.0) t_2))
(* (/ 15.0 8.0) (* (* t_2 t_0) t_0))))))
double code(double x) {
double t_0 = 1.0 / fabs(x);
double t_1 = (t_0 * t_0) * t_0;
double t_2 = (t_1 * t_0) * t_0;
return ((1.0 / sqrt(((double) M_PI))) * exp((fabs(x) * fabs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)));
}
public static double code(double x) {
double t_0 = 1.0 / Math.abs(x);
double t_1 = (t_0 * t_0) * t_0;
double t_2 = (t_1 * t_0) * t_0;
return ((1.0 / Math.sqrt(Math.PI)) * Math.exp((Math.abs(x) * Math.abs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)));
}
def code(x): t_0 = 1.0 / math.fabs(x) t_1 = (t_0 * t_0) * t_0 t_2 = (t_1 * t_0) * t_0 return ((1.0 / math.sqrt(math.pi)) * math.exp((math.fabs(x) * math.fabs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0)))
function code(x) t_0 = Float64(1.0 / abs(x)) t_1 = Float64(Float64(t_0 * t_0) * t_0) t_2 = Float64(Float64(t_1 * t_0) * t_0) return Float64(Float64(Float64(1.0 / sqrt(pi)) * exp(Float64(abs(x) * abs(x)))) * Float64(Float64(Float64(t_0 + Float64(Float64(1.0 / 2.0) * t_1)) + Float64(Float64(3.0 / 4.0) * t_2)) + Float64(Float64(15.0 / 8.0) * Float64(Float64(t_2 * t_0) * t_0)))) end
function tmp = code(x) t_0 = 1.0 / abs(x); t_1 = (t_0 * t_0) * t_0; t_2 = (t_1 * t_0) * t_0; tmp = ((1.0 / sqrt(pi)) * exp((abs(x) * abs(x)))) * (((t_0 + ((1.0 / 2.0) * t_1)) + ((3.0 / 4.0) * t_2)) + ((15.0 / 8.0) * ((t_2 * t_0) * t_0))); end
code[x_] := Block[{t$95$0 = N[(1.0 / N[Abs[x], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(t$95$0 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, N[(N[(N[(1.0 / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[Exp[N[(N[Abs[x], $MachinePrecision] * N[Abs[x], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[(N[(t$95$0 + N[(N[(1.0 / 2.0), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(N[(3.0 / 4.0), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(N[(15.0 / 8.0), $MachinePrecision] * N[(N[(t$95$2 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \frac{1}{\left|x\right|}\\
t_1 := \left(t\_0 \cdot t\_0\right) \cdot t\_0\\
t_2 := \left(t\_1 \cdot t\_0\right) \cdot t\_0\\
\left(\frac{1}{\sqrt{\pi}} \cdot e^{\left|x\right| \cdot \left|x\right|}\right) \cdot \left(\left(\left(t\_0 + \frac{1}{2} \cdot t\_1\right) + \frac{3}{4} \cdot t\_2\right) + \frac{15}{8} \cdot \left(\left(t\_2 \cdot t\_0\right) \cdot t\_0\right)\right)
\end{array}
\end{array}
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (fma 0.75 (pow x -5.0) (/ (+ 1.0 (+ (/ 0.5 (pow x 2.0)) (/ 1.875 (pow x 6.0)))) x))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * fma(0.75, pow(x, -5.0), ((1.0 + ((0.5 / pow(x, 2.0)) + (1.875 / pow(x, 6.0)))) / x));
}
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * fma(0.75, (x ^ -5.0), Float64(Float64(1.0 + Float64(Float64(0.5 / (x ^ 2.0)) + Float64(1.875 / (x ^ 6.0)))) / x))) end
code[x_] := N[(N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(0.75 * N[Power[x, -5.0], $MachinePrecision] + N[(N[(1.0 + N[(N[(0.5 / N[Power[x, 2.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \mathsf{fma}\left(0.75, {x}^{-5}, \frac{1 + \left(\frac{0.5}{{x}^{2}} + \frac{1.875}{{x}^{6}}\right)}{x}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
metadata-eval100.0%
pow-prod-up100.0%
pow3100.0%
pow2100.0%
*-un-lft-identity100.0%
*-commutative100.0%
pow3100.0%
pow2100.0%
pow-prod-up100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
associate-/l*100.0%
add-sqr-sqrt100.0%
hypot-1-def100.0%
sqrt-div100.0%
sqrt-prod100.0%
add-sqr-sqrt100.0%
add-sqr-sqrt100.0%
hypot-1-def100.0%
sqrt-div100.0%
sqrt-prod100.0%
add-sqr-sqrt100.0%
Applied egg-rr100.0%
associate-*r/100.0%
hypot-undefine100.0%
hypot-undefine100.0%
rem-square-sqrt100.0%
metadata-eval100.0%
associate-*r/100.0%
associate-*l/100.0%
rem-square-sqrt100.0%
associate-/r*100.0%
unpow2100.0%
Simplified100.0%
Taylor expanded in x around inf 100.0%
associate-*r/100.0%
metadata-eval100.0%
Simplified100.0%
Final simplification100.0%
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (+ (/ 1.0 x) (+ (/ 0.75 (pow x 5.0)) (/ 1.875 (pow x 7.0))))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * ((1.0 / x) + ((0.75 / pow(x, 5.0)) + (1.875 / pow(x, 7.0))));
}
public static double code(double x) {
return (Math.exp((x * x)) / Math.sqrt(Math.PI)) * ((1.0 / x) + ((0.75 / Math.pow(x, 5.0)) + (1.875 / Math.pow(x, 7.0))));
}
def code(x): return (math.exp((x * x)) / math.sqrt(math.pi)) * ((1.0 / x) + ((0.75 / math.pow(x, 5.0)) + (1.875 / math.pow(x, 7.0))))
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * Float64(Float64(1.0 / x) + Float64(Float64(0.75 / (x ^ 5.0)) + Float64(1.875 / (x ^ 7.0))))) end
function tmp = code(x) tmp = (exp((x * x)) / sqrt(pi)) * ((1.0 / x) + ((0.75 / (x ^ 5.0)) + (1.875 / (x ^ 7.0)))); end
code[x_] := N[(N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 / x), $MachinePrecision] + N[(N[(0.75 / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision] + N[(1.875 / N[Power[x, 7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \left(\frac{1}{x} + \left(\frac{0.75}{{x}^{5}} + \frac{1.875}{{x}^{7}}\right)\right)
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
metadata-eval100.0%
pow-prod-up100.0%
pow3100.0%
pow2100.0%
*-un-lft-identity100.0%
*-commutative100.0%
pow3100.0%
pow2100.0%
pow-prod-up100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
Taylor expanded in x around inf 99.7%
rem-square-sqrt99.7%
fabs-sqr99.7%
rem-square-sqrt99.7%
associate-*r/99.7%
metadata-eval99.7%
Simplified99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (* (/ (exp (* x x)) (sqrt PI)) (+ (/ 1.0 x) (* 0.75 (pow x -5.0)))))
double code(double x) {
return (exp((x * x)) / sqrt(((double) M_PI))) * ((1.0 / x) + (0.75 * pow(x, -5.0)));
}
public static double code(double x) {
return (Math.exp((x * x)) / Math.sqrt(Math.PI)) * ((1.0 / x) + (0.75 * Math.pow(x, -5.0)));
}
def code(x): return (math.exp((x * x)) / math.sqrt(math.pi)) * ((1.0 / x) + (0.75 * math.pow(x, -5.0)))
function code(x) return Float64(Float64(exp(Float64(x * x)) / sqrt(pi)) * Float64(Float64(1.0 / x) + Float64(0.75 * (x ^ -5.0)))) end
function tmp = code(x) tmp = (exp((x * x)) / sqrt(pi)) * ((1.0 / x) + (0.75 * (x ^ -5.0))); end
code[x_] := N[(N[(N[Exp[N[(x * x), $MachinePrecision]], $MachinePrecision] / N[Sqrt[Pi], $MachinePrecision]), $MachinePrecision] * N[(N[(1.0 / x), $MachinePrecision] + N[(0.75 * N[Power[x, -5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{e^{x \cdot x}}{\sqrt{\pi}} \cdot \left(\frac{1}{x} + 0.75 \cdot {x}^{-5}\right)
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
metadata-eval100.0%
pow-prod-up100.0%
pow3100.0%
pow2100.0%
*-un-lft-identity100.0%
*-commutative100.0%
pow3100.0%
pow2100.0%
pow-prod-up100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
fma-undefine99.7%
+-commutative99.7%
add-sqr-sqrt99.7%
fabs-sqr99.7%
add-sqr-sqrt99.7%
*-rgt-identity99.7%
Applied egg-rr99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (* (sqrt (/ 1.0 PI)) (/ (exp (pow x 2.0)) x)))
double code(double x) {
return sqrt((1.0 / ((double) M_PI))) * (exp(pow(x, 2.0)) / x);
}
public static double code(double x) {
return Math.sqrt((1.0 / Math.PI)) * (Math.exp(Math.pow(x, 2.0)) / x);
}
def code(x): return math.sqrt((1.0 / math.pi)) * (math.exp(math.pow(x, 2.0)) / x)
function code(x) return Float64(sqrt(Float64(1.0 / pi)) * Float64(exp((x ^ 2.0)) / x)) end
function tmp = code(x) tmp = sqrt((1.0 / pi)) * (exp((x ^ 2.0)) / x); end
code[x_] := N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] * N[(N[Exp[N[Power[x, 2.0], $MachinePrecision]], $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{1}{\pi}} \cdot \frac{e^{{x}^{2}}}{x}
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
metadata-eval100.0%
pow-prod-up100.0%
pow3100.0%
pow2100.0%
*-un-lft-identity100.0%
*-commutative100.0%
pow3100.0%
pow2100.0%
pow-prod-up100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
Taylor expanded in x around inf 99.7%
rem-square-sqrt99.7%
fabs-sqr99.7%
rem-square-sqrt99.7%
Simplified99.7%
Final simplification99.7%
(FPCore (x) :precision binary64 (* 0.75 (/ (sqrt (/ 1.0 PI)) (pow x 5.0))))
double code(double x) {
return 0.75 * (sqrt((1.0 / ((double) M_PI))) / pow(x, 5.0));
}
public static double code(double x) {
return 0.75 * (Math.sqrt((1.0 / Math.PI)) / Math.pow(x, 5.0));
}
def code(x): return 0.75 * (math.sqrt((1.0 / math.pi)) / math.pow(x, 5.0))
function code(x) return Float64(0.75 * Float64(sqrt(Float64(1.0 / pi)) / (x ^ 5.0))) end
function tmp = code(x) tmp = 0.75 * (sqrt((1.0 / pi)) / (x ^ 5.0)); end
code[x_] := N[(0.75 * N[(N[Sqrt[N[(1.0 / Pi), $MachinePrecision]], $MachinePrecision] / N[Power[x, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
0.75 \cdot \frac{\sqrt{\frac{1}{\pi}}}{{x}^{5}}
\end{array}
Initial program 100.0%
Simplified100.0%
add-log-exp100.0%
*-un-lft-identity100.0%
log-prod100.0%
metadata-eval100.0%
add-log-exp100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
+-lft-identity100.0%
Simplified100.0%
metadata-eval100.0%
pow-prod-up100.0%
pow3100.0%
pow2100.0%
*-un-lft-identity100.0%
*-commutative100.0%
pow3100.0%
pow2100.0%
pow-prod-up100.0%
metadata-eval100.0%
inv-pow100.0%
pow-pow100.0%
add-sqr-sqrt100.0%
fabs-sqr100.0%
add-sqr-sqrt100.0%
metadata-eval100.0%
Applied egg-rr100.0%
Taylor expanded in x around inf 99.7%
Taylor expanded in x around 0 1.8%
associate-*l/1.8%
*-lft-identity1.8%
Simplified1.8%
Final simplification1.8%
herbie shell --seed 2024072
(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)))))))