Average Error: 32.0 → 0.1
Time: 7.6s
Precision: binary64
\[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
\[\begin{array}{l} t_0 := \sqrt[3]{\mathsf{hypot}\left(re, im\right)}\\ \log \left({\left({\left(t_0 \cdot \left(t_0 \cdot t_0\right)\right)}^{\left(\sqrt{\frac{1}{\log 10}}\right)}\right)}^{\left(\frac{1}{\sqrt{\log 10}}\right)}\right) \end{array} \]
\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10}
\begin{array}{l}
t_0 := \sqrt[3]{\mathsf{hypot}\left(re, im\right)}\\
\log \left({\left({\left(t_0 \cdot \left(t_0 \cdot t_0\right)\right)}^{\left(\sqrt{\frac{1}{\log 10}}\right)}\right)}^{\left(\frac{1}{\sqrt{\log 10}}\right)}\right)
\end{array}
(FPCore (re im)
 :precision binary64
 (/ (log (sqrt (+ (* re re) (* im im)))) (log 10.0)))
(FPCore (re im)
 :precision binary64
 (let* ((t_0 (cbrt (hypot re im))))
   (log
    (pow
     (pow (* t_0 (* t_0 t_0)) (sqrt (/ 1.0 (log 10.0))))
     (/ 1.0 (sqrt (log 10.0)))))))
double code(double re, double im) {
	return log(sqrt((re * re) + (im * im))) / log(10.0);
}
double code(double re, double im) {
	double t_0 = cbrt(hypot(re, im));
	return log(pow(pow((t_0 * (t_0 * t_0)), sqrt(1.0 / log(10.0))), (1.0 / sqrt(log(10.0)))));
}

Error

Bits error versus re

Bits error versus im

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 32.0

    \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
  2. Simplified0.6

    \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
  3. Applied add-sqr-sqrt_binary640.6

    \[\leadsto \frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\color{blue}{\sqrt{\log 10} \cdot \sqrt{\log 10}}} \]
  4. Applied pow1_binary640.6

    \[\leadsto \frac{\log \color{blue}{\left({\left(\mathsf{hypot}\left(re, im\right)\right)}^{1}\right)}}{\sqrt{\log 10} \cdot \sqrt{\log 10}} \]
  5. Applied log-pow_binary640.6

    \[\leadsto \frac{\color{blue}{1 \cdot \log \left(\mathsf{hypot}\left(re, im\right)\right)}}{\sqrt{\log 10} \cdot \sqrt{\log 10}} \]
  6. Applied times-frac_binary640.6

    \[\leadsto \color{blue}{\frac{1}{\sqrt{\log 10}} \cdot \frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\sqrt{\log 10}}} \]
  7. Applied add-log-exp_binary640.6

    \[\leadsto \frac{1}{\sqrt{\log 10}} \cdot \color{blue}{\log \left(e^{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\sqrt{\log 10}}}\right)} \]
  8. Simplified0.3

    \[\leadsto \frac{1}{\sqrt{\log 10}} \cdot \log \color{blue}{\left({\left(\mathsf{hypot}\left(re, im\right)\right)}^{\left(\sqrt{\frac{1}{\log 10}}\right)}\right)} \]
  9. Applied add-log-exp_binary640.3

    \[\leadsto \color{blue}{\log \left(e^{\frac{1}{\sqrt{\log 10}} \cdot \log \left({\left(\mathsf{hypot}\left(re, im\right)\right)}^{\left(\sqrt{\frac{1}{\log 10}}\right)}\right)}\right)} \]
  10. Simplified0.1

    \[\leadsto \log \color{blue}{\left({\left({\left(\mathsf{hypot}\left(re, im\right)\right)}^{\left(\sqrt{\frac{1}{\log 10}}\right)}\right)}^{\left(\frac{1}{\sqrt{\log 10}}\right)}\right)} \]
  11. Applied add-cube-cbrt_binary640.1

    \[\leadsto \log \left({\left({\color{blue}{\left(\left(\sqrt[3]{\mathsf{hypot}\left(re, im\right)} \cdot \sqrt[3]{\mathsf{hypot}\left(re, im\right)}\right) \cdot \sqrt[3]{\mathsf{hypot}\left(re, im\right)}\right)}}^{\left(\sqrt{\frac{1}{\log 10}}\right)}\right)}^{\left(\frac{1}{\sqrt{\log 10}}\right)}\right) \]
  12. Final simplification0.1

    \[\leadsto \log \left({\left({\left(\sqrt[3]{\mathsf{hypot}\left(re, im\right)} \cdot \left(\sqrt[3]{\mathsf{hypot}\left(re, im\right)} \cdot \sqrt[3]{\mathsf{hypot}\left(re, im\right)}\right)\right)}^{\left(\sqrt{\frac{1}{\log 10}}\right)}\right)}^{\left(\frac{1}{\sqrt{\log 10}}\right)}\right) \]

Reproduce

herbie shell --seed 2021340 
(FPCore (re im)
  :name "math.log10 on complex, real part"
  :precision binary64
  (/ (log (sqrt (+ (* re re) (* im im)))) (log 10.0)))