Average Error: 0.1 → 0.1
Time: 6.1s
Precision: binary64
\[x \leq 0.5\]
\[\left|\frac{1}{\sqrt{\pi}} \cdot \left(\left(\left(2 \cdot \left|x\right| + \frac{2}{3} \cdot \left(\left(\left|x\right| \cdot \left|x\right|\right) \cdot \left|x\right|\right)\right) + \frac{1}{5} \cdot \left(\left(\left(\left(\left|x\right| \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right)\right) + \frac{1}{21} \cdot \left(\left(\left(\left(\left(\left(\left|x\right| \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right)\right)\right| \]
↓
\[\begin{array}{l} t_0 := \sqrt{\frac{1}{\pi}}\\ \left|0.047619047619047616 \cdot \left(t_0 \cdot {\left(\left|x\right|\right)}^{7}\right) + \left(0.6666666666666666 \cdot \left(t_0 \cdot \left(\left|x\right| \cdot {x}^{2}\right)\right) + \left(0.2 \cdot \left(t_0 \cdot {\left(\left|x\right|\right)}^{5}\right) + 2 \cdot \left(t_0 \cdot \left|x\right|\right)\right)\right)\right| \end{array} \]
\left|\frac{1}{\sqrt{\pi}} \cdot \left(\left(\left(2 \cdot \left|x\right| + \frac{2}{3} \cdot \left(\left(\left|x\right| \cdot \left|x\right|\right) \cdot \left|x\right|\right)\right) + \frac{1}{5} \cdot \left(\left(\left(\left(\left|x\right| \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right)\right) + \frac{1}{21} \cdot \left(\left(\left(\left(\left(\left(\left|x\right| \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right)\right)\right|
↓
\begin{array}{l}
t_0 := \sqrt{\frac{1}{\pi}}\\
\left|0.047619047619047616 \cdot \left(t_0 \cdot {\left(\left|x\right|\right)}^{7}\right) + \left(0.6666666666666666 \cdot \left(t_0 \cdot \left(\left|x\right| \cdot {x}^{2}\right)\right) + \left(0.2 \cdot \left(t_0 \cdot {\left(\left|x\right|\right)}^{5}\right) + 2 \cdot \left(t_0 \cdot \left|x\right|\right)\right)\right)\right|
\end{array}

(FPCore (x)
 :precision binary64
 (fabs
  (*
   (/ 1.0 (sqrt PI))
   (+
    (+
     (+ (* 2.0 (fabs x)) (* (/ 2.0 3.0) (* (* (fabs x) (fabs x)) (fabs x))))
     (*
      (/ 1.0 5.0)
      (* (* (* (* (fabs x) (fabs x)) (fabs x)) (fabs x)) (fabs x))))
    (*
     (/ 1.0 21.0)
     (*
      (* (* (* (* (* (fabs x) (fabs x)) (fabs x)) (fabs x)) (fabs x)) (fabs x))
      (fabs x)))))))
↓
(FPCore (x)
 :precision binary64
 (let* ((t_0 (sqrt (/ 1.0 PI))))
   (fabs
    (+
     (* 0.047619047619047616 (* t_0 (pow (fabs x) 7.0)))
     (+
      (* 0.6666666666666666 (* t_0 (* (fabs x) (pow x 2.0))))
      (+ (* 0.2 (* t_0 (pow (fabs x) 5.0))) (* 2.0 (* t_0 (fabs x)))))))))
double code(double x) {
	return fabs((1.0 / sqrt((double) M_PI)) * ((((2.0 * fabs(x)) + ((2.0 / 3.0) * ((fabs(x) * fabs(x)) * fabs(x)))) + ((1.0 / 5.0) * ((((fabs(x) * fabs(x)) * fabs(x)) * fabs(x)) * fabs(x)))) + ((1.0 / 21.0) * ((((((fabs(x) * fabs(x)) * fabs(x)) * fabs(x)) * fabs(x)) * fabs(x)) * fabs(x)))));
}
↓
double code(double x) {
	double t_0 = sqrt(1.0 / ((double) M_PI));
	return fabs((0.047619047619047616 * (t_0 * pow(fabs(x), 7.0))) + ((0.6666666666666666 * (t_0 * (fabs(x) * pow(x, 2.0)))) + ((0.2 * (t_0 * pow(fabs(x), 5.0))) + (2.0 * (t_0 * fabs(x))))));
}

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.1

    \[\left|\frac{1}{\sqrt{\pi}} \cdot \left(\left(\left(2 \cdot \left|x\right| + \frac{2}{3} \cdot \left(\left(\left|x\right| \cdot \left|x\right|\right) \cdot \left|x\right|\right)\right) + \frac{1}{5} \cdot \left(\left(\left(\left(\left|x\right| \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right)\right) + \frac{1}{21} \cdot \left(\left(\left(\left(\left(\left(\left|x\right| \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right) \cdot \left|x\right|\right)\right)\right| \]

  2. Taylor expanded around 0 0.1

    \[\leadsto \left|\color{blue}{\sqrt{\frac{1}{\pi}} \cdot \left(0.047619047619047616 \cdot {\left(\left|x\right|\right)}^{7} + \left(2 \cdot \left|x\right| + \left(0.6666666666666666 \cdot {\left(\left|x\right|\right)}^{3} + 0.2 \cdot {\left(\left|x\right|\right)}^{5}\right)\right)\right)}\right| \]

  3. Simplified0.1

    \[\leadsto \left|\color{blue}{\sqrt{\frac{1}{\pi}} \cdot \left(0.2 \cdot {\left(\left|x\right|\right)}^{5} + \left(\left|x\right| \cdot \left(0.6666666666666666 \cdot \left(x \cdot x\right) + 2\right) + 0.047619047619047616 \cdot {\left(\left|x\right|\right)}^{7}\right)\right)}\right| \]

  4. Taylor expanded around -inf 0.1

    \[\leadsto \left|\color{blue}{0.047619047619047616 \cdot \left(\sqrt{\frac{1}{\pi}} \cdot {\left(\left|x\right|\right)}^{7}\right) + \left(0.6666666666666666 \cdot \left(\left(\left|x\right| \cdot {x}^{2}\right) \cdot \sqrt{\frac{1}{\pi}}\right) + \left(0.2 \cdot \left(\sqrt{\frac{1}{\pi}} \cdot {\left(\left|x\right|\right)}^{5}\right) + 2 \cdot \left(\sqrt{\frac{1}{\pi}} \cdot \left|x\right|\right)\right)\right)}\right| \]

  5. Final simplification0.1

    \[\leadsto \left|0.047619047619047616 \cdot \left(\sqrt{\frac{1}{\pi}} \cdot {\left(\left|x\right|\right)}^{7}\right) + \left(0.6666666666666666 \cdot \left(\sqrt{\frac{1}{\pi}} \cdot \left(\left|x\right| \cdot {x}^{2}\right)\right) + \left(0.2 \cdot \left(\sqrt{\frac{1}{\pi}} \cdot {\left(\left|x\right|\right)}^{5}\right) + 2 \cdot \left(\sqrt{\frac{1}{\pi}} \cdot \left|x\right|\right)\right)\right)\right| \]

Reproduce

herbie shell --seed 2021198 
(FPCore (x)
  :name "Jmat.Real.erfi, branch x less than or equal to 0.5"
  :precision binary64
  :pre (<= x 0.5)
  (fabs (* (/ 1.0 (sqrt PI)) (+ (+ (+ (* 2.0 (fabs x)) (* (/ 2.0 3.0) (* (* (fabs x) (fabs x)) (fabs x)))) (* (/ 1.0 5.0) (* (* (* (* (fabs x) (fabs x)) (fabs x)) (fabs x)) (fabs x)))) (* (/ 1.0 21.0) (* (* (* (* (* (* (fabs x) (fabs x)) (fabs x)) (fabs x)) (fabs x)) (fabs x)) (fabs x)))))))