Average Error: 61.0 → 0.4
Time: 33.0s
Precision: 64
\[-1 \lt x \land x \lt 1\]
\[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)}\]
↓
\[\frac{\log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)} - \frac{1 \cdot x}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)}\]
\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)}
↓
\frac{\log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)} - \frac{1 \cdot x}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)}
double code(double x) {
	return ((double) (((double) log(((double) (1.0 - x)))) / ((double) log(((double) (1.0 + x))))));
}
↓
double code(double x) {
	return ((double) (((double) (((double) (((double) log(1.0)) - ((double) (0.5 * ((double) (((double) pow(x, 2.0)) / ((double) pow(1.0, 2.0)))))))) / ((double) fma(x, 1.0, ((double) (((double) log(1.0)) - ((double) (0.5 * ((double) (((double) pow(x, 2.0)) / ((double) pow(1.0, 2.0)))))))))))) - ((double) (((double) (1.0 * x)) / ((double) fma(x, 1.0, ((double) (((double) log(1.0)) - ((double) (0.5 * ((double) (((double) pow(x, 2.0)) / ((double) pow(1.0, 2.0))))))))))))));
}

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original61.0
Target0.3
Herbie0.4
\[-\left(\left(\left(1 + x\right) + \frac{x \cdot x}{2}\right) + 0.416666666666666685 \cdot {x}^{3}\right)\]

Derivation

  1. Initial program 61.0

    \[\frac{\log \left(1 - x\right)}{\log \left(1 + x\right)}\]

  2. Taylor expanded around 0 60.4

    \[\leadsto \frac{\log \left(1 - x\right)}{\color{blue}{\left(1 \cdot x + \log 1\right) - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}}}\]

  3. Simplified60.4

    \[\leadsto \frac{\log \left(1 - x\right)}{\color{blue}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)}}\]

  4. Taylor expanded around 0 0.4

    \[\leadsto \frac{\color{blue}{\log 1 - \left(1 \cdot x + \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)}}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)}\]
  5. Using strategy rm

  6. Applied +-commutative0.4

    \[\leadsto \frac{\log 1 - \color{blue}{\left(\frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}} + 1 \cdot x\right)}}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)}\]

  7. Applied associate--r+0.4

    \[\leadsto \frac{\color{blue}{\left(\log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right) - 1 \cdot x}}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)}\]

  8. Applied div-sub0.4

    \[\leadsto \color{blue}{\frac{\log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)} - \frac{1 \cdot x}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)}}\]

  9. Final simplification0.4

    \[\leadsto \frac{\log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)} - \frac{1 \cdot x}{\mathsf{fma}\left(x, 1, \log 1 - \frac{1}{2} \cdot \frac{{x}^{2}}{{1}^{2}}\right)}\]

Reproduce

herbie shell --seed 2020113 +o rules:numerics
(FPCore (x)
  :name "qlog (example 3.10)"
  :precision binary64
  :pre (and (< -1 x) (< x 1))

  :herbie-target
  (- (+ (+ (+ 1 x) (/ (* x x) 2)) (* 0.4166666666666667 (pow x 3))))

  (/ (log (- 1 x)) (log (+ 1 x))))