Numeric.SpecFunctions:stirlingError from math-functions-0.1.5.2

Percentage Accurate: 99.8% → 99.9%
Time: 9.2s
Alternatives: 11
Speedup: TODO×

Specification

?
\[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]

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 11 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.

Target

Original99.8%
Target99.8%
Herbie99.9%
\[\left(\left(y + x\right) - z\right) - \left(y + 0.5\right) \cdot \log y \]

Alternative 1?

\[\mathsf{fma}\left(\log y, -0.5 - y, y + \left(x - z\right)\right) \]
Derivation
  1. Initial program 99.9%

    \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
  2. Step-by-step derivation
    1. associate--l+99.9%

      \[\leadsto \color{blue}{\left(x - \left(y + 0.5\right) \cdot \log y\right) + \left(y - z\right)} \]
    2. sub-neg99.9%

      \[\leadsto \color{blue}{\left(x + \left(-\left(y + 0.5\right) \cdot \log y\right)\right)} + \left(y - z\right) \]
    3. +-commutative99.9%

      \[\leadsto \color{blue}{\left(\left(-\left(y + 0.5\right) \cdot \log y\right) + x\right)} + \left(y - z\right) \]
    4. associate-+l+99.9%

      \[\leadsto \color{blue}{\left(-\left(y + 0.5\right) \cdot \log y\right) + \left(x + \left(y - z\right)\right)} \]
    5. *-commutative99.9%

      \[\leadsto \left(-\color{blue}{\log y \cdot \left(y + 0.5\right)}\right) + \left(x + \left(y - z\right)\right) \]
    6. distribute-rgt-neg-in99.9%

      \[\leadsto \color{blue}{\log y \cdot \left(-\left(y + 0.5\right)\right)} + \left(x + \left(y - z\right)\right) \]
    7. fma-def99.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\log y, -\left(y + 0.5\right), x + \left(y - z\right)\right)} \]
    8. neg-sub099.9%

      \[\leadsto \mathsf{fma}\left(\log y, \color{blue}{0 - \left(y + 0.5\right)}, x + \left(y - z\right)\right) \]
    9. +-commutative99.9%

      \[\leadsto \mathsf{fma}\left(\log y, 0 - \color{blue}{\left(0.5 + y\right)}, x + \left(y - z\right)\right) \]
    10. associate--r+99.9%

      \[\leadsto \mathsf{fma}\left(\log y, \color{blue}{\left(0 - 0.5\right) - y}, x + \left(y - z\right)\right) \]
    11. metadata-eval99.9%

      \[\leadsto \mathsf{fma}\left(\log y, \color{blue}{-0.5} - y, x + \left(y - z\right)\right) \]
    12. associate-+r-99.9%

      \[\leadsto \mathsf{fma}\left(\log y, -0.5 - y, \color{blue}{\left(x + y\right) - z}\right) \]
    13. +-commutative99.9%

      \[\leadsto \mathsf{fma}\left(\log y, -0.5 - y, \color{blue}{\left(y + x\right)} - z\right) \]
    14. associate-+r-99.9%

      \[\leadsto \mathsf{fma}\left(\log y, -0.5 - y, \color{blue}{y + \left(x - z\right)}\right) \]
  3. Simplified99.9%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\log y, -0.5 - y, y + \left(x - z\right)\right)} \]
  4. Final simplification99.9%

    \[\leadsto \mathsf{fma}\left(\log y, -0.5 - y, y + \left(x - z\right)\right) \]

Alternative 2?

\[\begin{array}{l} t_0 := y \cdot \left(1 - \log y\right) - z\\ \mathbf{if}\;x \leq -1.35 \cdot 10^{+15}:\\ \;\;\;\;x - z\\ \mathbf{elif}\;x \leq 3.8 \cdot 10^{-222}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;x \leq 1.85 \cdot 10^{-70}:\\ \;\;\;\;\log y \cdot -0.5 - z\\ \mathbf{elif}\;x \leq 8.5 \cdot 10^{+43}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;y + \left(x - y \cdot \log y\right)\\ \end{array} \]
Derivation
  1. Split input into 4 regimes
  2. if x < -1.35e15

    1. Initial program 100.0%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in x around inf 89.3%

      \[\leadsto \color{blue}{x} - z \]

    if -1.35e15 < x < 3.79999999999999997e-222 or 1.85e-70 < x < 8.5e43

    1. Initial program 99.8%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in y around inf 81.1%

      \[\leadsto \color{blue}{y \cdot \left(1 - -1 \cdot \log \left(\frac{1}{y}\right)\right)} - z \]
    3. Step-by-step derivation
      1. *-commutative81.1%

        \[\leadsto y \cdot \left(1 - \color{blue}{\log \left(\frac{1}{y}\right) \cdot -1}\right) - z \]
      2. log-rec81.1%

        \[\leadsto y \cdot \left(1 - \color{blue}{\left(-\log y\right)} \cdot -1\right) - z \]
      3. cancel-sign-sub81.1%

        \[\leadsto y \cdot \color{blue}{\left(1 + \log y \cdot -1\right)} - z \]
      4. *-commutative81.1%

        \[\leadsto y \cdot \left(1 + \color{blue}{-1 \cdot \log y}\right) - z \]
      5. mul-1-neg81.1%

        \[\leadsto y \cdot \left(1 + \color{blue}{\left(-\log y\right)}\right) - z \]
      6. log-rec81.1%

        \[\leadsto y \cdot \left(1 + \color{blue}{\log \left(\frac{1}{y}\right)}\right) - z \]
      7. log-rec81.1%

        \[\leadsto y \cdot \left(1 + \color{blue}{\left(-\log y\right)}\right) - z \]
      8. sub-neg81.1%

        \[\leadsto y \cdot \color{blue}{\left(1 - \log y\right)} - z \]
    4. Simplified81.1%

      \[\leadsto \color{blue}{y \cdot \left(1 - \log y\right)} - z \]

    if 3.79999999999999997e-222 < x < 1.85e-70

    1. Initial program 99.9%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in y around 0 79.1%

      \[\leadsto \color{blue}{\left(x - 0.5 \cdot \log y\right)} - z \]
    3. Taylor expanded in x around 0 79.1%

      \[\leadsto \color{blue}{-0.5 \cdot \log y} - z \]
    4. Step-by-step derivation
      1. *-commutative79.1%

        \[\leadsto \color{blue}{\log y \cdot -0.5} - z \]
    5. Simplified79.1%

      \[\leadsto \color{blue}{\log y \cdot -0.5} - z \]

    if 8.5e43 < x

    1. Initial program 99.9%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in y around inf 99.9%

      \[\leadsto \left(\left(x - \color{blue}{-1 \cdot \left(y \cdot \log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
    3. Step-by-step derivation
      1. mul-1-neg99.9%

        \[\leadsto \left(\left(x - \color{blue}{\left(-y \cdot \log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
      2. distribute-rgt-neg-in99.9%

        \[\leadsto \left(\left(x - \color{blue}{y \cdot \left(-\log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
      3. log-rec99.9%

        \[\leadsto \left(\left(x - y \cdot \left(-\color{blue}{\left(-\log y\right)}\right)\right) + y\right) - z \]
      4. remove-double-neg99.9%

        \[\leadsto \left(\left(x - y \cdot \color{blue}{\log y}\right) + y\right) - z \]
    4. Simplified99.9%

      \[\leadsto \left(\left(x - \color{blue}{y \cdot \log y}\right) + y\right) - z \]
    5. Step-by-step derivation
      1. associate--l+99.9%

        \[\leadsto \color{blue}{\left(x - y \cdot \log y\right) + \left(y - z\right)} \]
      2. add-cube-cbrt97.9%

        \[\leadsto \color{blue}{\left(\sqrt[3]{x - y \cdot \log y} \cdot \sqrt[3]{x - y \cdot \log y}\right) \cdot \sqrt[3]{x - y \cdot \log y}} + \left(y - z\right) \]
      3. fma-def97.9%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt[3]{x - y \cdot \log y} \cdot \sqrt[3]{x - y \cdot \log y}, \sqrt[3]{x - y \cdot \log y}, y - z\right)} \]
      4. pow297.9%

        \[\leadsto \mathsf{fma}\left(\color{blue}{{\left(\sqrt[3]{x - y \cdot \log y}\right)}^{2}}, \sqrt[3]{x - y \cdot \log y}, y - z\right) \]
    6. Applied egg-rr97.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left({\left(\sqrt[3]{x - y \cdot \log y}\right)}^{2}, \sqrt[3]{x - y \cdot \log y}, y - z\right)} \]
    7. Taylor expanded in z around 0 92.3%

      \[\leadsto \color{blue}{y + {1}^{0.3333333333333333} \cdot \left(x - y \cdot \log y\right)} \]
    8. Step-by-step derivation
      1. pow-base-192.3%

        \[\leadsto y + \color{blue}{1} \cdot \left(x - y \cdot \log y\right) \]
      2. *-lft-identity92.3%

        \[\leadsto y + \color{blue}{\left(x - y \cdot \log y\right)} \]
    9. Simplified92.3%

      \[\leadsto \color{blue}{y + \left(x - y \cdot \log y\right)} \]
  3. Recombined 4 regimes into one program.
  4. Final simplification85.5%

    \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.35 \cdot 10^{+15}:\\ \;\;\;\;x - z\\ \mathbf{elif}\;x \leq 3.8 \cdot 10^{-222}:\\ \;\;\;\;y \cdot \left(1 - \log y\right) - z\\ \mathbf{elif}\;x \leq 1.85 \cdot 10^{-70}:\\ \;\;\;\;\log y \cdot -0.5 - z\\ \mathbf{elif}\;x \leq 8.5 \cdot 10^{+43}:\\ \;\;\;\;y \cdot \left(1 - \log y\right) - z\\ \mathbf{else}:\\ \;\;\;\;y + \left(x - y \cdot \log y\right)\\ \end{array} \]

Alternative 3?

\[\begin{array}{l} \mathbf{if}\;y \leq 3 \cdot 10^{+15}:\\ \;\;\;\;\left(x - \log y \cdot 0.5\right) - z\\ \mathbf{elif}\;y \leq 1.4 \cdot 10^{+74} \lor \neg \left(y \leq 5.8 \cdot 10^{+138}\right):\\ \;\;\;\;y + \left(x - y \cdot \log y\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(1 - \log y\right) - z\\ \end{array} \]
Derivation
  1. Split input into 3 regimes
  2. if y < 3e15

    1. Initial program 100.0%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in y around 0 98.0%

      \[\leadsto \color{blue}{\left(x - 0.5 \cdot \log y\right)} - z \]

    if 3e15 < y < 1.40000000000000001e74 or 5.80000000000000019e138 < y

    1. Initial program 99.7%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in y around inf 99.7%

      \[\leadsto \left(\left(x - \color{blue}{-1 \cdot \left(y \cdot \log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
    3. Step-by-step derivation
      1. mul-1-neg99.7%

        \[\leadsto \left(\left(x - \color{blue}{\left(-y \cdot \log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
      2. distribute-rgt-neg-in99.7%

        \[\leadsto \left(\left(x - \color{blue}{y \cdot \left(-\log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
      3. log-rec99.7%

        \[\leadsto \left(\left(x - y \cdot \left(-\color{blue}{\left(-\log y\right)}\right)\right) + y\right) - z \]
      4. remove-double-neg99.7%

        \[\leadsto \left(\left(x - y \cdot \color{blue}{\log y}\right) + y\right) - z \]
    4. Simplified99.7%

      \[\leadsto \left(\left(x - \color{blue}{y \cdot \log y}\right) + y\right) - z \]
    5. Step-by-step derivation
      1. associate--l+99.7%

        \[\leadsto \color{blue}{\left(x - y \cdot \log y\right) + \left(y - z\right)} \]
      2. add-cube-cbrt98.3%

        \[\leadsto \color{blue}{\left(\sqrt[3]{x - y \cdot \log y} \cdot \sqrt[3]{x - y \cdot \log y}\right) \cdot \sqrt[3]{x - y \cdot \log y}} + \left(y - z\right) \]
      3. fma-def98.2%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt[3]{x - y \cdot \log y} \cdot \sqrt[3]{x - y \cdot \log y}, \sqrt[3]{x - y \cdot \log y}, y - z\right)} \]
      4. pow298.2%

        \[\leadsto \mathsf{fma}\left(\color{blue}{{\left(\sqrt[3]{x - y \cdot \log y}\right)}^{2}}, \sqrt[3]{x - y \cdot \log y}, y - z\right) \]
    6. Applied egg-rr98.2%

      \[\leadsto \color{blue}{\mathsf{fma}\left({\left(\sqrt[3]{x - y \cdot \log y}\right)}^{2}, \sqrt[3]{x - y \cdot \log y}, y - z\right)} \]
    7. Taylor expanded in z around 0 88.2%

      \[\leadsto \color{blue}{y + {1}^{0.3333333333333333} \cdot \left(x - y \cdot \log y\right)} \]
    8. Step-by-step derivation
      1. pow-base-188.2%

        \[\leadsto y + \color{blue}{1} \cdot \left(x - y \cdot \log y\right) \]
      2. *-lft-identity88.2%

        \[\leadsto y + \color{blue}{\left(x - y \cdot \log y\right)} \]
    9. Simplified88.2%

      \[\leadsto \color{blue}{y + \left(x - y \cdot \log y\right)} \]

    if 1.40000000000000001e74 < y < 5.80000000000000019e138

    1. Initial program 99.8%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in y around inf 80.4%

      \[\leadsto \color{blue}{y \cdot \left(1 - -1 \cdot \log \left(\frac{1}{y}\right)\right)} - z \]
    3. Step-by-step derivation
      1. *-commutative80.4%

        \[\leadsto y \cdot \left(1 - \color{blue}{\log \left(\frac{1}{y}\right) \cdot -1}\right) - z \]
      2. log-rec80.4%

        \[\leadsto y \cdot \left(1 - \color{blue}{\left(-\log y\right)} \cdot -1\right) - z \]
      3. cancel-sign-sub80.4%

        \[\leadsto y \cdot \color{blue}{\left(1 + \log y \cdot -1\right)} - z \]
      4. *-commutative80.4%

        \[\leadsto y \cdot \left(1 + \color{blue}{-1 \cdot \log y}\right) - z \]
      5. mul-1-neg80.4%

        \[\leadsto y \cdot \left(1 + \color{blue}{\left(-\log y\right)}\right) - z \]
      6. log-rec80.4%

        \[\leadsto y \cdot \left(1 + \color{blue}{\log \left(\frac{1}{y}\right)}\right) - z \]
      7. log-rec80.4%

        \[\leadsto y \cdot \left(1 + \color{blue}{\left(-\log y\right)}\right) - z \]
      8. sub-neg80.4%

        \[\leadsto y \cdot \color{blue}{\left(1 - \log y\right)} - z \]
    4. Simplified80.4%

      \[\leadsto \color{blue}{y \cdot \left(1 - \log y\right)} - z \]
  3. Recombined 3 regimes into one program.
  4. Final simplification93.5%

    \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq 3 \cdot 10^{+15}:\\ \;\;\;\;\left(x - \log y \cdot 0.5\right) - z\\ \mathbf{elif}\;y \leq 1.4 \cdot 10^{+74} \lor \neg \left(y \leq 5.8 \cdot 10^{+138}\right):\\ \;\;\;\;y + \left(x - y \cdot \log y\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(1 - \log y\right) - z\\ \end{array} \]

Alternative 4?

\[\begin{array}{l} \mathbf{if}\;z \leq -7.5 \cdot 10^{+75}:\\ \;\;\;\;x - z\\ \mathbf{elif}\;z \leq 4.15 \cdot 10^{+36}:\\ \;\;\;\;y + \left(x - y \cdot \log y\right)\\ \mathbf{else}:\\ \;\;\;\;x - z\\ \end{array} \]
Derivation
  1. Split input into 2 regimes
  2. if z < -7.4999999999999995e75 or 4.15000000000000011e36 < z

    1. Initial program 99.9%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in x around inf 85.0%

      \[\leadsto \color{blue}{x} - z \]

    if -7.4999999999999995e75 < z < 4.15000000000000011e36

    1. Initial program 99.9%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in y around inf 78.8%

      \[\leadsto \left(\left(x - \color{blue}{-1 \cdot \left(y \cdot \log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
    3. Step-by-step derivation
      1. mul-1-neg78.8%

        \[\leadsto \left(\left(x - \color{blue}{\left(-y \cdot \log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
      2. distribute-rgt-neg-in78.8%

        \[\leadsto \left(\left(x - \color{blue}{y \cdot \left(-\log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
      3. log-rec78.8%

        \[\leadsto \left(\left(x - y \cdot \left(-\color{blue}{\left(-\log y\right)}\right)\right) + y\right) - z \]
      4. remove-double-neg78.8%

        \[\leadsto \left(\left(x - y \cdot \color{blue}{\log y}\right) + y\right) - z \]
    4. Simplified78.8%

      \[\leadsto \left(\left(x - \color{blue}{y \cdot \log y}\right) + y\right) - z \]
    5. Step-by-step derivation
      1. associate--l+78.8%

        \[\leadsto \color{blue}{\left(x - y \cdot \log y\right) + \left(y - z\right)} \]
      2. add-cube-cbrt77.5%

        \[\leadsto \color{blue}{\left(\sqrt[3]{x - y \cdot \log y} \cdot \sqrt[3]{x - y \cdot \log y}\right) \cdot \sqrt[3]{x - y \cdot \log y}} + \left(y - z\right) \]
      3. fma-def77.5%

        \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt[3]{x - y \cdot \log y} \cdot \sqrt[3]{x - y \cdot \log y}, \sqrt[3]{x - y \cdot \log y}, y - z\right)} \]
      4. pow277.5%

        \[\leadsto \mathsf{fma}\left(\color{blue}{{\left(\sqrt[3]{x - y \cdot \log y}\right)}^{2}}, \sqrt[3]{x - y \cdot \log y}, y - z\right) \]
    6. Applied egg-rr77.5%

      \[\leadsto \color{blue}{\mathsf{fma}\left({\left(\sqrt[3]{x - y \cdot \log y}\right)}^{2}, \sqrt[3]{x - y \cdot \log y}, y - z\right)} \]
    7. Taylor expanded in z around 0 77.5%

      \[\leadsto \color{blue}{y + {1}^{0.3333333333333333} \cdot \left(x - y \cdot \log y\right)} \]
    8. Step-by-step derivation
      1. pow-base-177.5%

        \[\leadsto y + \color{blue}{1} \cdot \left(x - y \cdot \log y\right) \]
      2. *-lft-identity77.5%

        \[\leadsto y + \color{blue}{\left(x - y \cdot \log y\right)} \]
    9. Simplified77.5%

      \[\leadsto \color{blue}{y + \left(x - y \cdot \log y\right)} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification80.5%

    \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -7.5 \cdot 10^{+75}:\\ \;\;\;\;x - z\\ \mathbf{elif}\;z \leq 4.15 \cdot 10^{+36}:\\ \;\;\;\;y + \left(x - y \cdot \log y\right)\\ \mathbf{else}:\\ \;\;\;\;x - z\\ \end{array} \]

Alternative 5?

\[\begin{array}{l} \mathbf{if}\;y \leq 0.28:\\ \;\;\;\;\left(x - \log y \cdot 0.5\right) - z\\ \mathbf{else}:\\ \;\;\;\;\left(y + \left(x - y \cdot \log y\right)\right) - z\\ \end{array} \]
Derivation
  1. Split input into 2 regimes
  2. if y < 0.28000000000000003

    1. Initial program 100.0%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in y around 0 99.1%

      \[\leadsto \color{blue}{\left(x - 0.5 \cdot \log y\right)} - z \]

    if 0.28000000000000003 < y

    1. Initial program 99.8%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in y around inf 99.4%

      \[\leadsto \left(\left(x - \color{blue}{-1 \cdot \left(y \cdot \log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
    3. Step-by-step derivation
      1. mul-1-neg99.4%

        \[\leadsto \left(\left(x - \color{blue}{\left(-y \cdot \log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
      2. distribute-rgt-neg-in99.4%

        \[\leadsto \left(\left(x - \color{blue}{y \cdot \left(-\log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
      3. log-rec99.4%

        \[\leadsto \left(\left(x - y \cdot \left(-\color{blue}{\left(-\log y\right)}\right)\right) + y\right) - z \]
      4. remove-double-neg99.4%

        \[\leadsto \left(\left(x - y \cdot \color{blue}{\log y}\right) + y\right) - z \]
    4. Simplified99.4%

      \[\leadsto \left(\left(x - \color{blue}{y \cdot \log y}\right) + y\right) - z \]
  3. Recombined 2 regimes into one program.
  4. Final simplification99.2%

    \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq 0.28:\\ \;\;\;\;\left(x - \log y \cdot 0.5\right) - z\\ \mathbf{else}:\\ \;\;\;\;\left(y + \left(x - y \cdot \log y\right)\right) - z\\ \end{array} \]

Alternative 6?

\[\left(y + \left(x - \log y \cdot \left(y + 0.5\right)\right)\right) - z \]
Derivation
  1. Initial program 99.9%

    \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
  2. Final simplification99.9%

    \[\leadsto \left(y + \left(x - \log y \cdot \left(y + 0.5\right)\right)\right) - z \]

Alternative 7?

\[\left(\left(y + x\right) - \log y \cdot \left(y + 0.5\right)\right) - z \]
Derivation
  1. Initial program 99.9%

    \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
  2. Step-by-step derivation
    1. +-commutative99.9%

      \[\leadsto \color{blue}{\left(y + \left(x - \left(y + 0.5\right) \cdot \log y\right)\right)} - z \]
    2. associate-+r-99.9%

      \[\leadsto \color{blue}{\left(\left(y + x\right) - \left(y + 0.5\right) \cdot \log y\right)} - z \]
  3. Applied egg-rr99.9%

    \[\leadsto \color{blue}{\left(\left(y + x\right) - \left(y + 0.5\right) \cdot \log y\right)} - z \]
  4. Final simplification99.9%

    \[\leadsto \left(\left(y + x\right) - \log y \cdot \left(y + 0.5\right)\right) - z \]

Alternative 8?

\[\begin{array}{l} \mathbf{if}\;x \leq -44:\\ \;\;\;\;x - z\\ \mathbf{elif}\;x \leq 1.3 \cdot 10^{+15}:\\ \;\;\;\;\log y \cdot -0.5 - z\\ \mathbf{else}:\\ \;\;\;\;x - z\\ \end{array} \]
Derivation
  1. Split input into 2 regimes
  2. if x < -44 or 1.3e15 < x

    1. Initial program 99.9%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in x around inf 84.7%

      \[\leadsto \color{blue}{x} - z \]

    if -44 < x < 1.3e15

    1. Initial program 99.8%

      \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
    2. Taylor expanded in y around 0 66.3%

      \[\leadsto \color{blue}{\left(x - 0.5 \cdot \log y\right)} - z \]
    3. Taylor expanded in x around 0 65.4%

      \[\leadsto \color{blue}{-0.5 \cdot \log y} - z \]
    4. Step-by-step derivation
      1. *-commutative65.4%

        \[\leadsto \color{blue}{\log y \cdot -0.5} - z \]
    5. Simplified65.4%

      \[\leadsto \color{blue}{\log y \cdot -0.5} - z \]
  3. Recombined 2 regimes into one program.
  4. Final simplification75.3%

    \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -44:\\ \;\;\;\;x - z\\ \mathbf{elif}\;x \leq 1.3 \cdot 10^{+15}:\\ \;\;\;\;\log y \cdot -0.5 - z\\ \mathbf{else}:\\ \;\;\;\;x - z\\ \end{array} \]

Alternative 9?

\[x - z \]
Derivation
  1. Initial program 99.9%

    \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
  2. Taylor expanded in x around inf 63.2%

    \[\leadsto \color{blue}{x} - z \]
  3. Final simplification63.2%

    \[\leadsto x - z \]

Alternative 10?

\[-z \]
Derivation
  1. Initial program 99.9%

    \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
  2. Step-by-step derivation
    1. associate--l+99.9%

      \[\leadsto \color{blue}{\left(x - \left(y + 0.5\right) \cdot \log y\right) + \left(y - z\right)} \]
    2. sub-neg99.9%

      \[\leadsto \color{blue}{\left(x + \left(-\left(y + 0.5\right) \cdot \log y\right)\right)} + \left(y - z\right) \]
    3. +-commutative99.9%

      \[\leadsto \color{blue}{\left(\left(-\left(y + 0.5\right) \cdot \log y\right) + x\right)} + \left(y - z\right) \]
    4. associate-+l+99.9%

      \[\leadsto \color{blue}{\left(-\left(y + 0.5\right) \cdot \log y\right) + \left(x + \left(y - z\right)\right)} \]
    5. *-commutative99.9%

      \[\leadsto \left(-\color{blue}{\log y \cdot \left(y + 0.5\right)}\right) + \left(x + \left(y - z\right)\right) \]
    6. distribute-rgt-neg-in99.9%

      \[\leadsto \color{blue}{\log y \cdot \left(-\left(y + 0.5\right)\right)} + \left(x + \left(y - z\right)\right) \]
    7. fma-def99.9%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\log y, -\left(y + 0.5\right), x + \left(y - z\right)\right)} \]
    8. neg-sub099.9%

      \[\leadsto \mathsf{fma}\left(\log y, \color{blue}{0 - \left(y + 0.5\right)}, x + \left(y - z\right)\right) \]
    9. +-commutative99.9%

      \[\leadsto \mathsf{fma}\left(\log y, 0 - \color{blue}{\left(0.5 + y\right)}, x + \left(y - z\right)\right) \]
    10. associate--r+99.9%

      \[\leadsto \mathsf{fma}\left(\log y, \color{blue}{\left(0 - 0.5\right) - y}, x + \left(y - z\right)\right) \]
    11. metadata-eval99.9%

      \[\leadsto \mathsf{fma}\left(\log y, \color{blue}{-0.5} - y, x + \left(y - z\right)\right) \]
    12. associate-+r-99.9%

      \[\leadsto \mathsf{fma}\left(\log y, -0.5 - y, \color{blue}{\left(x + y\right) - z}\right) \]
    13. +-commutative99.9%

      \[\leadsto \mathsf{fma}\left(\log y, -0.5 - y, \color{blue}{\left(y + x\right)} - z\right) \]
    14. associate-+r-99.9%

      \[\leadsto \mathsf{fma}\left(\log y, -0.5 - y, \color{blue}{y + \left(x - z\right)}\right) \]
  3. Simplified99.9%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\log y, -0.5 - y, y + \left(x - z\right)\right)} \]
  4. Taylor expanded in z around inf 29.9%

    \[\leadsto \color{blue}{-1 \cdot z} \]
  5. Step-by-step derivation
    1. mul-1-neg29.9%

      \[\leadsto \color{blue}{-z} \]
  6. Simplified29.9%

    \[\leadsto \color{blue}{-z} \]
  7. Final simplification29.9%

    \[\leadsto -z \]

Alternative 11?

\[y \]
Derivation
  1. Initial program 99.9%

    \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z \]
  2. Taylor expanded in y around inf 87.2%

    \[\leadsto \left(\left(x - \color{blue}{-1 \cdot \left(y \cdot \log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
  3. Step-by-step derivation
    1. mul-1-neg87.2%

      \[\leadsto \left(\left(x - \color{blue}{\left(-y \cdot \log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
    2. distribute-rgt-neg-in87.2%

      \[\leadsto \left(\left(x - \color{blue}{y \cdot \left(-\log \left(\frac{1}{y}\right)\right)}\right) + y\right) - z \]
    3. log-rec87.2%

      \[\leadsto \left(\left(x - y \cdot \left(-\color{blue}{\left(-\log y\right)}\right)\right) + y\right) - z \]
    4. remove-double-neg87.2%

      \[\leadsto \left(\left(x - y \cdot \color{blue}{\log y}\right) + y\right) - z \]
  4. Simplified87.2%

    \[\leadsto \left(\left(x - \color{blue}{y \cdot \log y}\right) + y\right) - z \]
  5. Step-by-step derivation
    1. associate--l+87.2%

      \[\leadsto \color{blue}{\left(x - y \cdot \log y\right) + \left(y - z\right)} \]
    2. add-cube-cbrt86.1%

      \[\leadsto \color{blue}{\left(\sqrt[3]{x - y \cdot \log y} \cdot \sqrt[3]{x - y \cdot \log y}\right) \cdot \sqrt[3]{x - y \cdot \log y}} + \left(y - z\right) \]
    3. fma-def86.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt[3]{x - y \cdot \log y} \cdot \sqrt[3]{x - y \cdot \log y}, \sqrt[3]{x - y \cdot \log y}, y - z\right)} \]
    4. pow286.1%

      \[\leadsto \mathsf{fma}\left(\color{blue}{{\left(\sqrt[3]{x - y \cdot \log y}\right)}^{2}}, \sqrt[3]{x - y \cdot \log y}, y - z\right) \]
  6. Applied egg-rr86.1%

    \[\leadsto \color{blue}{\mathsf{fma}\left({\left(\sqrt[3]{x - y \cdot \log y}\right)}^{2}, \sqrt[3]{x - y \cdot \log y}, y - z\right)} \]
  7. Taylor expanded in y around inf 2.6%

    \[\leadsto \color{blue}{y} \]
  8. Final simplification2.6%

    \[\leadsto y \]

Reproduce

?
herbie shell --seed 2023166 
(FPCore (x y z)
  :name "Numeric.SpecFunctions:stirlingError from math-functions-0.1.5.2"
  :precision binary64

  :herbie-target
  (- (- (+ y x) z) (* (+ y 0.5) (log y)))

  (- (+ (- x (* (+ y 0.5) (log y))) y) z))