Average Error: 0.3 → 0.3
Time: 9.7s
Precision: 64
\[\left(\left(\log \left(x + y\right) + \log z\right) - t\right) + \left(a - 0.5\right) \cdot \log t\]
↓
\[\left(\left(\log \left(x + y\right) + \log z\right) + \log t \cdot \left(a - 0.5\right)\right) + \left(-t\right)\]
\left(\left(\log \left(x + y\right) + \log z\right) - t\right) + \left(a - 0.5\right) \cdot \log t
↓
\left(\left(\log \left(x + y\right) + \log z\right) + \log t \cdot \left(a - 0.5\right)\right) + \left(-t\right)
double code(double x, double y, double z, double t, double a) {
	return (((log((x + y)) + log(z)) - t) + ((a - 0.5) * log(t)));
}
↓
double code(double x, double y, double z, double t, double a) {
	return (((log((x + y)) + log(z)) + (log(t) * (a - 0.5))) + -t);
}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Bits error versus t

Bits error versus a

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original0.3
Target0.3
Herbie0.3
\[\log \left(x + y\right) + \left(\left(\log z - t\right) + \left(a - 0.5\right) \cdot \log t\right)\]

Derivation

  1. Initial program 0.3

    \[\left(\left(\log \left(x + y\right) + \log z\right) - t\right) + \left(a - 0.5\right) \cdot \log t\]
  2. Using strategy rm

  3. Applied +-commutative0.3

    \[\leadsto \color{blue}{\left(a - 0.5\right) \cdot \log t + \left(\left(\log \left(x + y\right) + \log z\right) - t\right)}\]
  4. Using strategy rm

  5. Applied flip--16.1

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

  6. Applied associate-*l/16.3

    \[\leadsto \color{blue}{\frac{\left(a \cdot a - 0.5 \cdot 0.5\right) \cdot \log t}{a + 0.5}} + \left(\left(\log \left(x + y\right) + \log z\right) - t\right)\]
  7. Using strategy rm

  8. Applied *-commutative16.3

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

  9. Applied associate-/l*16.1

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

  10. Simplified0.3

    \[\leadsto \frac{\log t}{\color{blue}{\frac{1}{a - 0.5}}} + \left(\left(\log \left(x + y\right) + \log z\right) - t\right)\]
  11. Using strategy rm

  12. Applied sub-neg0.3

    \[\leadsto \frac{\log t}{\frac{1}{a - 0.5}} + \color{blue}{\left(\left(\log \left(x + y\right) + \log z\right) + \left(-t\right)\right)}\]

  13. Applied associate-+r+0.3

    \[\leadsto \color{blue}{\left(\frac{\log t}{\frac{1}{a - 0.5}} + \left(\log \left(x + y\right) + \log z\right)\right) + \left(-t\right)}\]

  14. Simplified0.3

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

  15. Final simplification0.3

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

Reproduce

herbie shell --seed 2020078 
(FPCore (x y z t a)
  :name "Numeric.SpecFunctions:logGammaL from math-functions-0.1.5.2"
  :precision binary64

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

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