math.log10 on complex, real part

Percentage Accurate: 51.1% → 99.5%
Time: 9.5s
Alternatives: 8
Speedup: 1.5×

Specification

?
\[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]

Your Program's Arguments

Results

Enter valid numbers for all inputs

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 8 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Alternative 1: 99.5% accurate, 0.5× speedup?

\[\frac{{\log 10}^{-0.5}}{\sqrt{\log 10}} \cdot \log \left(\mathsf{hypot}\left(re, im\right)\right) \]
Derivation
  1. Initial program 53.7%

    \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
  2. Step-by-step derivation
    1. hypot-def99.1%

      \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
  3. Simplified99.1%

    \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
  4. Step-by-step derivation
    1. *-un-lft-identity99.1%

      \[\leadsto \frac{\color{blue}{1 \cdot \log \left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
    2. add-sqr-sqrt99.1%

      \[\leadsto \frac{1 \cdot \log \left(\mathsf{hypot}\left(re, im\right)\right)}{\color{blue}{\sqrt{\log 10} \cdot \sqrt{\log 10}}} \]
    3. times-frac99.2%

      \[\leadsto \color{blue}{\frac{1}{\sqrt{\log 10}} \cdot \frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\sqrt{\log 10}}} \]
  5. Applied egg-rr99.2%

    \[\leadsto \color{blue}{\frac{1}{\sqrt{\log 10}} \cdot \frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\sqrt{\log 10}}} \]
  6. Step-by-step derivation
    1. clear-num99.1%

      \[\leadsto \frac{1}{\sqrt{\log 10}} \cdot \color{blue}{\frac{1}{\frac{\sqrt{\log 10}}{\log \left(\mathsf{hypot}\left(re, im\right)\right)}}} \]
    2. un-div-inv99.1%

      \[\leadsto \color{blue}{\frac{\frac{1}{\sqrt{\log 10}}}{\frac{\sqrt{\log 10}}{\log \left(\mathsf{hypot}\left(re, im\right)\right)}}} \]
    3. pow1/299.1%

      \[\leadsto \frac{\frac{1}{\color{blue}{{\log 10}^{0.5}}}}{\frac{\sqrt{\log 10}}{\log \left(\mathsf{hypot}\left(re, im\right)\right)}} \]
    4. pow-flip99.1%

      \[\leadsto \frac{\color{blue}{{\log 10}^{\left(-0.5\right)}}}{\frac{\sqrt{\log 10}}{\log \left(\mathsf{hypot}\left(re, im\right)\right)}} \]
    5. metadata-eval99.1%

      \[\leadsto \frac{{\log 10}^{\color{blue}{-0.5}}}{\frac{\sqrt{\log 10}}{\log \left(\mathsf{hypot}\left(re, im\right)\right)}} \]
  7. Applied egg-rr99.1%

    \[\leadsto \color{blue}{\frac{{\log 10}^{-0.5}}{\frac{\sqrt{\log 10}}{\log \left(\mathsf{hypot}\left(re, im\right)\right)}}} \]
  8. Step-by-step derivation
    1. associate-/r/99.5%

      \[\leadsto \color{blue}{\frac{{\log 10}^{-0.5}}{\sqrt{\log 10}} \cdot \log \left(\mathsf{hypot}\left(re, im\right)\right)} \]
  9. Simplified99.5%

    \[\leadsto \color{blue}{\frac{{\log 10}^{-0.5}}{\sqrt{\log 10}} \cdot \log \left(\mathsf{hypot}\left(re, im\right)\right)} \]
  10. Final simplification99.5%

    \[\leadsto \frac{{\log 10}^{-0.5}}{\sqrt{\log 10}} \cdot \log \left(\mathsf{hypot}\left(re, im\right)\right) \]

Alternative 2: 99.1% accurate, 1.0× speedup?

\[\left(1 + \frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right) + -1 \]
Derivation
  1. Initial program 53.7%

    \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
  2. Step-by-step derivation
    1. hypot-def99.1%

      \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
  3. Simplified99.1%

    \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
  4. Step-by-step derivation
    1. expm1-log1p-u67.9%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right)\right)} \]
    2. expm1-udef67.8%

      \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right)} - 1} \]
    3. log1p-udef67.9%

      \[\leadsto e^{\color{blue}{\log \left(1 + \frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right)}} - 1 \]
    4. add-exp-log99.1%

      \[\leadsto \color{blue}{\left(1 + \frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right)} - 1 \]
  5. Applied egg-rr99.1%

    \[\leadsto \color{blue}{\left(1 + \frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right) - 1} \]
  6. Final simplification99.1%

    \[\leadsto \left(1 + \frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right) + -1 \]

Alternative 3: 99.1% accurate, 1.0× speedup?

\[\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10} \]
Derivation
  1. Initial program 53.7%

    \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
  2. Step-by-step derivation
    1. hypot-def99.1%

      \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
  3. Simplified99.1%

    \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
  4. Final simplification99.1%

    \[\leadsto \frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10} \]

Alternative 4: 42.9% accurate, 1.5× speedup?

\[\begin{array}{l} \mathbf{if}\;re \leq -1.08 \cdot 10^{-44}:\\ \;\;\;\;\left(1 + \frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}\right) + -1\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\frac{\log 10}{\log im}}\\ \end{array} \]
Derivation
  1. Split input into 2 regimes
  2. if re < -1.07999999999999994e-44

    1. Initial program 39.0%

      \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
    2. Step-by-step derivation
      1. hypot-def99.1%

        \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
    3. Simplified99.1%

      \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
    4. Step-by-step derivation
      1. expm1-log1p-u90.2%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right)\right)} \]
    5. Applied egg-rr90.2%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right)\right)} \]
    6. Taylor expanded in re around -inf 72.0%

      \[\leadsto \mathsf{expm1}\left(\color{blue}{\log \left(1 + -1 \cdot \frac{\log \left(\frac{-1}{re}\right)}{\log 10}\right)}\right) \]
    7. Step-by-step derivation
      1. log1p-def71.9%

        \[\leadsto \mathsf{expm1}\left(\color{blue}{\mathsf{log1p}\left(-1 \cdot \frac{\log \left(\frac{-1}{re}\right)}{\log 10}\right)}\right) \]
      2. mul-1-neg71.9%

        \[\leadsto \mathsf{expm1}\left(\mathsf{log1p}\left(\color{blue}{-\frac{\log \left(\frac{-1}{re}\right)}{\log 10}}\right)\right) \]
      3. distribute-neg-frac71.9%

        \[\leadsto \mathsf{expm1}\left(\mathsf{log1p}\left(\color{blue}{\frac{-\log \left(\frac{-1}{re}\right)}{\log 10}}\right)\right) \]
    8. Simplified71.9%

      \[\leadsto \mathsf{expm1}\left(\color{blue}{\mathsf{log1p}\left(\frac{-\log \left(\frac{-1}{re}\right)}{\log 10}\right)}\right) \]
    9. Step-by-step derivation
      1. expm1-udef71.9%

        \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{-\log \left(\frac{-1}{re}\right)}{\log 10}\right)} - 1} \]
      2. log1p-udef72.0%

        \[\leadsto e^{\color{blue}{\log \left(1 + \frac{-\log \left(\frac{-1}{re}\right)}{\log 10}\right)}} - 1 \]
      3. add-exp-log80.5%

        \[\leadsto \color{blue}{\left(1 + \frac{-\log \left(\frac{-1}{re}\right)}{\log 10}\right)} - 1 \]
      4. neg-log80.5%

        \[\leadsto \left(1 + \frac{\color{blue}{\log \left(\frac{1}{\frac{-1}{re}}\right)}}{\log 10}\right) - 1 \]
      5. frac-2neg80.5%

        \[\leadsto \left(1 + \frac{\log \left(\frac{1}{\color{blue}{\frac{--1}{-re}}}\right)}{\log 10}\right) - 1 \]
      6. metadata-eval80.5%

        \[\leadsto \left(1 + \frac{\log \left(\frac{1}{\frac{\color{blue}{1}}{-re}}\right)}{\log 10}\right) - 1 \]
      7. remove-double-div80.5%

        \[\leadsto \left(1 + \frac{\log \color{blue}{\left(-re\right)}}{\log 10}\right) - 1 \]
      8. log1p-expm1-u80.5%

        \[\leadsto \left(1 + \frac{\log \left(-re\right)}{\color{blue}{\mathsf{log1p}\left(\mathsf{expm1}\left(\log 10\right)\right)}}\right) - 1 \]
      9. expm1-udef80.5%

        \[\leadsto \left(1 + \frac{\log \left(-re\right)}{\mathsf{log1p}\left(\color{blue}{e^{\log 10} - 1}\right)}\right) - 1 \]
      10. add-exp-log80.5%

        \[\leadsto \left(1 + \frac{\log \left(-re\right)}{\mathsf{log1p}\left(\color{blue}{10} - 1\right)}\right) - 1 \]
      11. metadata-eval80.5%

        \[\leadsto \left(1 + \frac{\log \left(-re\right)}{\mathsf{log1p}\left(\color{blue}{9}\right)}\right) - 1 \]
    10. Applied egg-rr80.5%

      \[\leadsto \color{blue}{\left(1 + \frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}\right) - 1} \]

    if -1.07999999999999994e-44 < re

    1. Initial program 57.3%

      \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
    2. Step-by-step derivation
      1. hypot-def99.1%

        \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
    3. Simplified99.1%

      \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
    4. Taylor expanded in re around 0 34.4%

      \[\leadsto \color{blue}{\frac{\log im}{\log 10}} \]
    5. Step-by-step derivation
      1. clear-num34.4%

        \[\leadsto \color{blue}{\frac{1}{\frac{\log 10}{\log im}}} \]
      2. inv-pow34.4%

        \[\leadsto \color{blue}{{\left(\frac{\log 10}{\log im}\right)}^{-1}} \]
    6. Applied egg-rr34.4%

      \[\leadsto \color{blue}{{\left(\frac{\log 10}{\log im}\right)}^{-1}} \]
    7. Step-by-step derivation
      1. unpow-134.4%

        \[\leadsto \color{blue}{\frac{1}{\frac{\log 10}{\log im}}} \]
    8. Simplified34.4%

      \[\leadsto \color{blue}{\frac{1}{\frac{\log 10}{\log im}}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification43.5%

    \[\leadsto \begin{array}{l} \mathbf{if}\;re \leq -1.08 \cdot 10^{-44}:\\ \;\;\;\;\left(1 + \frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}\right) + -1\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\frac{\log 10}{\log im}}\\ \end{array} \]

Alternative 5: 42.9% accurate, 1.5× speedup?

\[\begin{array}{l} \mathbf{if}\;re \leq -1.35 \cdot 10^{-44}:\\ \;\;\;\;\frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\frac{\log 10}{\log im}}\\ \end{array} \]
Derivation
  1. Split input into 2 regimes
  2. if re < -1.35e-44

    1. Initial program 39.0%

      \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
    2. Step-by-step derivation
      1. hypot-def99.1%

        \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
    3. Simplified99.1%

      \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
    4. Step-by-step derivation
      1. expm1-log1p-u90.2%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right)\right)} \]
    5. Applied egg-rr90.2%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right)\right)} \]
    6. Taylor expanded in re around -inf 72.0%

      \[\leadsto \mathsf{expm1}\left(\color{blue}{\log \left(1 + -1 \cdot \frac{\log \left(\frac{-1}{re}\right)}{\log 10}\right)}\right) \]
    7. Step-by-step derivation
      1. log1p-def71.9%

        \[\leadsto \mathsf{expm1}\left(\color{blue}{\mathsf{log1p}\left(-1 \cdot \frac{\log \left(\frac{-1}{re}\right)}{\log 10}\right)}\right) \]
      2. mul-1-neg71.9%

        \[\leadsto \mathsf{expm1}\left(\mathsf{log1p}\left(\color{blue}{-\frac{\log \left(\frac{-1}{re}\right)}{\log 10}}\right)\right) \]
      3. distribute-neg-frac71.9%

        \[\leadsto \mathsf{expm1}\left(\mathsf{log1p}\left(\color{blue}{\frac{-\log \left(\frac{-1}{re}\right)}{\log 10}}\right)\right) \]
    8. Simplified71.9%

      \[\leadsto \mathsf{expm1}\left(\color{blue}{\mathsf{log1p}\left(\frac{-\log \left(\frac{-1}{re}\right)}{\log 10}\right)}\right) \]
    9. Step-by-step derivation
      1. expm1-log1p-u80.5%

        \[\leadsto \color{blue}{\frac{-\log \left(\frac{-1}{re}\right)}{\log 10}} \]
      2. *-un-lft-identity80.5%

        \[\leadsto \color{blue}{1 \cdot \frac{-\log \left(\frac{-1}{re}\right)}{\log 10}} \]
      3. neg-log80.5%

        \[\leadsto 1 \cdot \frac{\color{blue}{\log \left(\frac{1}{\frac{-1}{re}}\right)}}{\log 10} \]
      4. frac-2neg80.5%

        \[\leadsto 1 \cdot \frac{\log \left(\frac{1}{\color{blue}{\frac{--1}{-re}}}\right)}{\log 10} \]
      5. metadata-eval80.5%

        \[\leadsto 1 \cdot \frac{\log \left(\frac{1}{\frac{\color{blue}{1}}{-re}}\right)}{\log 10} \]
      6. remove-double-div80.5%

        \[\leadsto 1 \cdot \frac{\log \color{blue}{\left(-re\right)}}{\log 10} \]
      7. log1p-expm1-u80.5%

        \[\leadsto 1 \cdot \frac{\log \left(-re\right)}{\color{blue}{\mathsf{log1p}\left(\mathsf{expm1}\left(\log 10\right)\right)}} \]
      8. expm1-udef80.5%

        \[\leadsto 1 \cdot \frac{\log \left(-re\right)}{\mathsf{log1p}\left(\color{blue}{e^{\log 10} - 1}\right)} \]
      9. add-exp-log80.5%

        \[\leadsto 1 \cdot \frac{\log \left(-re\right)}{\mathsf{log1p}\left(\color{blue}{10} - 1\right)} \]
      10. metadata-eval80.5%

        \[\leadsto 1 \cdot \frac{\log \left(-re\right)}{\mathsf{log1p}\left(\color{blue}{9}\right)} \]
    10. Applied egg-rr80.5%

      \[\leadsto \color{blue}{1 \cdot \frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}} \]
    11. Step-by-step derivation
      1. *-lft-identity80.5%

        \[\leadsto \color{blue}{\frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}} \]
    12. Simplified80.5%

      \[\leadsto \color{blue}{\frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}} \]

    if -1.35e-44 < re

    1. Initial program 57.3%

      \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
    2. Step-by-step derivation
      1. hypot-def99.1%

        \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
    3. Simplified99.1%

      \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
    4. Taylor expanded in re around 0 34.4%

      \[\leadsto \color{blue}{\frac{\log im}{\log 10}} \]
    5. Step-by-step derivation
      1. clear-num34.4%

        \[\leadsto \color{blue}{\frac{1}{\frac{\log 10}{\log im}}} \]
      2. inv-pow34.4%

        \[\leadsto \color{blue}{{\left(\frac{\log 10}{\log im}\right)}^{-1}} \]
    6. Applied egg-rr34.4%

      \[\leadsto \color{blue}{{\left(\frac{\log 10}{\log im}\right)}^{-1}} \]
    7. Step-by-step derivation
      1. unpow-134.4%

        \[\leadsto \color{blue}{\frac{1}{\frac{\log 10}{\log im}}} \]
    8. Simplified34.4%

      \[\leadsto \color{blue}{\frac{1}{\frac{\log 10}{\log im}}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification43.5%

    \[\leadsto \begin{array}{l} \mathbf{if}\;re \leq -1.35 \cdot 10^{-44}:\\ \;\;\;\;\frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\frac{\log 10}{\log im}}\\ \end{array} \]

Alternative 6: 42.9% accurate, 1.5× speedup?

\[\begin{array}{l} \mathbf{if}\;re \leq -1.3 \cdot 10^{-44}:\\ \;\;\;\;\frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{\log im}{\log 10}\\ \end{array} \]
Derivation
  1. Split input into 2 regimes
  2. if re < -1.2999999999999999e-44

    1. Initial program 39.0%

      \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
    2. Step-by-step derivation
      1. hypot-def99.1%

        \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
    3. Simplified99.1%

      \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
    4. Step-by-step derivation
      1. expm1-log1p-u90.2%

        \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right)\right)} \]
    5. Applied egg-rr90.2%

      \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}\right)\right)} \]
    6. Taylor expanded in re around -inf 72.0%

      \[\leadsto \mathsf{expm1}\left(\color{blue}{\log \left(1 + -1 \cdot \frac{\log \left(\frac{-1}{re}\right)}{\log 10}\right)}\right) \]
    7. Step-by-step derivation
      1. log1p-def71.9%

        \[\leadsto \mathsf{expm1}\left(\color{blue}{\mathsf{log1p}\left(-1 \cdot \frac{\log \left(\frac{-1}{re}\right)}{\log 10}\right)}\right) \]
      2. mul-1-neg71.9%

        \[\leadsto \mathsf{expm1}\left(\mathsf{log1p}\left(\color{blue}{-\frac{\log \left(\frac{-1}{re}\right)}{\log 10}}\right)\right) \]
      3. distribute-neg-frac71.9%

        \[\leadsto \mathsf{expm1}\left(\mathsf{log1p}\left(\color{blue}{\frac{-\log \left(\frac{-1}{re}\right)}{\log 10}}\right)\right) \]
    8. Simplified71.9%

      \[\leadsto \mathsf{expm1}\left(\color{blue}{\mathsf{log1p}\left(\frac{-\log \left(\frac{-1}{re}\right)}{\log 10}\right)}\right) \]
    9. Step-by-step derivation
      1. expm1-log1p-u80.5%

        \[\leadsto \color{blue}{\frac{-\log \left(\frac{-1}{re}\right)}{\log 10}} \]
      2. *-un-lft-identity80.5%

        \[\leadsto \color{blue}{1 \cdot \frac{-\log \left(\frac{-1}{re}\right)}{\log 10}} \]
      3. neg-log80.5%

        \[\leadsto 1 \cdot \frac{\color{blue}{\log \left(\frac{1}{\frac{-1}{re}}\right)}}{\log 10} \]
      4. frac-2neg80.5%

        \[\leadsto 1 \cdot \frac{\log \left(\frac{1}{\color{blue}{\frac{--1}{-re}}}\right)}{\log 10} \]
      5. metadata-eval80.5%

        \[\leadsto 1 \cdot \frac{\log \left(\frac{1}{\frac{\color{blue}{1}}{-re}}\right)}{\log 10} \]
      6. remove-double-div80.5%

        \[\leadsto 1 \cdot \frac{\log \color{blue}{\left(-re\right)}}{\log 10} \]
      7. log1p-expm1-u80.5%

        \[\leadsto 1 \cdot \frac{\log \left(-re\right)}{\color{blue}{\mathsf{log1p}\left(\mathsf{expm1}\left(\log 10\right)\right)}} \]
      8. expm1-udef80.5%

        \[\leadsto 1 \cdot \frac{\log \left(-re\right)}{\mathsf{log1p}\left(\color{blue}{e^{\log 10} - 1}\right)} \]
      9. add-exp-log80.5%

        \[\leadsto 1 \cdot \frac{\log \left(-re\right)}{\mathsf{log1p}\left(\color{blue}{10} - 1\right)} \]
      10. metadata-eval80.5%

        \[\leadsto 1 \cdot \frac{\log \left(-re\right)}{\mathsf{log1p}\left(\color{blue}{9}\right)} \]
    10. Applied egg-rr80.5%

      \[\leadsto \color{blue}{1 \cdot \frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}} \]
    11. Step-by-step derivation
      1. *-lft-identity80.5%

        \[\leadsto \color{blue}{\frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}} \]
    12. Simplified80.5%

      \[\leadsto \color{blue}{\frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}} \]

    if -1.2999999999999999e-44 < re

    1. Initial program 57.3%

      \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
    2. Step-by-step derivation
      1. hypot-def99.1%

        \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
    3. Simplified99.1%

      \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
    4. Taylor expanded in re around 0 34.4%

      \[\leadsto \color{blue}{\frac{\log im}{\log 10}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification43.6%

    \[\leadsto \begin{array}{l} \mathbf{if}\;re \leq -1.3 \cdot 10^{-44}:\\ \;\;\;\;\frac{\log \left(-re\right)}{\mathsf{log1p}\left(9\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{\log im}{\log 10}\\ \end{array} \]

Alternative 7: 3.0% accurate, 1.5× speedup?

\[\frac{\log im}{\log 0.1} \]
Derivation
  1. Initial program 53.7%

    \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
  2. Step-by-step derivation
    1. hypot-def99.1%

      \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
  3. Simplified99.1%

    \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
  4. Taylor expanded in re around 0 29.4%

    \[\leadsto \color{blue}{\frac{\log im}{\log 10}} \]
  5. Step-by-step derivation
    1. frac-2neg29.4%

      \[\leadsto \color{blue}{\frac{-\log im}{-\log 10}} \]
    2. div-inv29.2%

      \[\leadsto \color{blue}{\left(-\log im\right) \cdot \frac{1}{-\log 10}} \]
    3. neg-log29.3%

      \[\leadsto \left(-\log im\right) \cdot \frac{1}{\color{blue}{\log \left(\frac{1}{10}\right)}} \]
    4. metadata-eval29.3%

      \[\leadsto \left(-\log im\right) \cdot \frac{1}{\log \color{blue}{0.1}} \]
  6. Applied egg-rr29.3%

    \[\leadsto \color{blue}{\left(-\log im\right) \cdot \frac{1}{\log 0.1}} \]
  7. Step-by-step derivation
    1. log-rec29.3%

      \[\leadsto \color{blue}{\log \left(\frac{1}{im}\right)} \cdot \frac{1}{\log 0.1} \]
    2. associate-*r/29.3%

      \[\leadsto \color{blue}{\frac{\log \left(\frac{1}{im}\right) \cdot 1}{\log 0.1}} \]
    3. *-rgt-identity29.3%

      \[\leadsto \frac{\color{blue}{\log \left(\frac{1}{im}\right)}}{\log 0.1} \]
    4. log-rec29.3%

      \[\leadsto \frac{\color{blue}{-\log im}}{\log 0.1} \]
  8. Simplified29.3%

    \[\leadsto \color{blue}{\frac{-\log im}{\log 0.1}} \]
  9. Step-by-step derivation
    1. *-un-lft-identity29.3%

      \[\leadsto \frac{\color{blue}{1 \cdot \left(-\log im\right)}}{\log 0.1} \]
    2. add-cube-cbrt29.0%

      \[\leadsto \frac{1 \cdot \left(-\log im\right)}{\color{blue}{\left(\sqrt[3]{\log 0.1} \cdot \sqrt[3]{\log 0.1}\right) \cdot \sqrt[3]{\log 0.1}}} \]
    3. times-frac29.0%

      \[\leadsto \color{blue}{\frac{1}{\sqrt[3]{\log 0.1} \cdot \sqrt[3]{\log 0.1}} \cdot \frac{-\log im}{\sqrt[3]{\log 0.1}}} \]
    4. pow229.0%

      \[\leadsto \frac{1}{\color{blue}{{\left(\sqrt[3]{\log 0.1}\right)}^{2}}} \cdot \frac{-\log im}{\sqrt[3]{\log 0.1}} \]
    5. add-sqr-sqrt9.2%

      \[\leadsto \frac{1}{{\left(\sqrt[3]{\log 0.1}\right)}^{2}} \cdot \frac{\color{blue}{\sqrt{-\log im} \cdot \sqrt{-\log im}}}{\sqrt[3]{\log 0.1}} \]
    6. sqrt-unprod9.6%

      \[\leadsto \frac{1}{{\left(\sqrt[3]{\log 0.1}\right)}^{2}} \cdot \frac{\color{blue}{\sqrt{\left(-\log im\right) \cdot \left(-\log im\right)}}}{\sqrt[3]{\log 0.1}} \]
    7. sqr-neg9.6%

      \[\leadsto \frac{1}{{\left(\sqrt[3]{\log 0.1}\right)}^{2}} \cdot \frac{\sqrt{\color{blue}{\log im \cdot \log im}}}{\sqrt[3]{\log 0.1}} \]
    8. sqrt-unprod0.4%

      \[\leadsto \frac{1}{{\left(\sqrt[3]{\log 0.1}\right)}^{2}} \cdot \frac{\color{blue}{\sqrt{\log im} \cdot \sqrt{\log im}}}{\sqrt[3]{\log 0.1}} \]
    9. add-sqr-sqrt2.3%

      \[\leadsto \frac{1}{{\left(\sqrt[3]{\log 0.1}\right)}^{2}} \cdot \frac{\color{blue}{\log im}}{\sqrt[3]{\log 0.1}} \]
  10. Applied egg-rr2.3%

    \[\leadsto \color{blue}{\frac{1}{{\left(\sqrt[3]{\log 0.1}\right)}^{2}} \cdot \frac{\log im}{\sqrt[3]{\log 0.1}}} \]
  11. Step-by-step derivation
    1. associate-*l/2.3%

      \[\leadsto \color{blue}{\frac{1 \cdot \frac{\log im}{\sqrt[3]{\log 0.1}}}{{\left(\sqrt[3]{\log 0.1}\right)}^{2}}} \]
    2. *-lft-identity2.3%

      \[\leadsto \frac{\color{blue}{\frac{\log im}{\sqrt[3]{\log 0.1}}}}{{\left(\sqrt[3]{\log 0.1}\right)}^{2}} \]
    3. associate-/r*2.3%

      \[\leadsto \color{blue}{\frac{\log im}{\sqrt[3]{\log 0.1} \cdot {\left(\sqrt[3]{\log 0.1}\right)}^{2}}} \]
    4. unpow22.3%

      \[\leadsto \frac{\log im}{\sqrt[3]{\log 0.1} \cdot \color{blue}{\left(\sqrt[3]{\log 0.1} \cdot \sqrt[3]{\log 0.1}\right)}} \]
    5. rem-3cbrt-rft2.3%

      \[\leadsto \frac{\log im}{\color{blue}{\log 0.1}} \]
  12. Simplified2.3%

    \[\leadsto \color{blue}{\frac{\log im}{\log 0.1}} \]
  13. Final simplification2.3%

    \[\leadsto \frac{\log im}{\log 0.1} \]

Alternative 8: 26.9% accurate, 1.5× speedup?

\[\frac{\log im}{\log 10} \]
Derivation
  1. Initial program 53.7%

    \[\frac{\log \left(\sqrt{re \cdot re + im \cdot im}\right)}{\log 10} \]
  2. Step-by-step derivation
    1. hypot-def99.1%

      \[\leadsto \frac{\log \color{blue}{\left(\mathsf{hypot}\left(re, im\right)\right)}}{\log 10} \]
  3. Simplified99.1%

    \[\leadsto \color{blue}{\frac{\log \left(\mathsf{hypot}\left(re, im\right)\right)}{\log 10}} \]
  4. Taylor expanded in re around 0 29.4%

    \[\leadsto \color{blue}{\frac{\log im}{\log 10}} \]
  5. Final simplification29.4%

    \[\leadsto \frac{\log im}{\log 10} \]

Reproduce

?
herbie shell --seed 2023167 
(FPCore (re im)
  :name "math.log10 on complex, real part"
  :precision binary64
  (/ (log (sqrt (+ (* re re) (* im im)))) (log 10.0)))