Average Error: 3.8 → 0.6
Time: 2.1m
Precision: 64
Internal Precision: 1856
\[\frac{{\left(\frac{1}{1 + e^{-s}}\right)}^{c_p} \cdot {\left(1 - \frac{1}{1 + e^{-s}}\right)}^{c_n}}{{\left(\frac{1}{1 + e^{-t}}\right)}^{c_p} \cdot {\left(1 - \frac{1}{1 + e^{-t}}\right)}^{c_n}}\]
\[e^{c_p \cdot \left(\left(\left(\frac{1}{8} \cdot {t}^{2} + \log 2\right) - t \cdot \frac{1}{2}\right) - \log \left(1 + e^{-s}\right)\right) + c_n \cdot \left(\log \left(1 - \frac{1}{1 + e^{-s}}\right) - \log \left(1 - \frac{1}{e^{-t} + 1}\right)\right)}\]

Error

Bits error versus c_p

Bits error versus c_n

Bits error versus t

Bits error versus s

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original3.8
Target2.0
Herbie0.6
\[{\left(\frac{1 + e^{-t}}{1 + e^{-s}}\right)}^{c_p} \cdot {\left(\frac{1 + e^{t}}{1 + e^{s}}\right)}^{c_n}\]

Derivation

  1. Initial program 3.8

    \[\frac{{\left(\frac{1}{1 + e^{-s}}\right)}^{c_p} \cdot {\left(1 - \frac{1}{1 + e^{-s}}\right)}^{c_n}}{{\left(\frac{1}{1 + e^{-t}}\right)}^{c_p} \cdot {\left(1 - \frac{1}{1 + e^{-t}}\right)}^{c_n}}\]
  2. Initial simplification3.8

    \[\leadsto \frac{{\left(1 - \frac{1}{e^{-s} + 1}\right)}^{c_n}}{{\left(1 - \frac{1}{e^{-t} + 1}\right)}^{c_n}} \cdot \frac{{\left(\frac{1}{e^{-s} + 1}\right)}^{c_p}}{{\left(\frac{1}{e^{-t} + 1}\right)}^{c_p}}\]
  3. Using strategy rm
  4. Applied add-exp-log3.8

    \[\leadsto \frac{{\left(1 - \frac{1}{e^{-s} + 1}\right)}^{c_n}}{{\left(1 - \frac{1}{e^{-t} + 1}\right)}^{c_n}} \cdot \frac{{\left(\frac{1}{e^{-s} + 1}\right)}^{c_p}}{\color{blue}{e^{\log \left({\left(\frac{1}{e^{-t} + 1}\right)}^{c_p}\right)}}}\]
  5. Applied pow-to-exp3.8

    \[\leadsto \frac{{\left(1 - \frac{1}{e^{-s} + 1}\right)}^{c_n}}{{\left(1 - \frac{1}{e^{-t} + 1}\right)}^{c_n}} \cdot \frac{\color{blue}{e^{\log \left(\frac{1}{e^{-s} + 1}\right) \cdot c_p}}}{e^{\log \left({\left(\frac{1}{e^{-t} + 1}\right)}^{c_p}\right)}}\]
  6. Applied div-exp3.8

    \[\leadsto \frac{{\left(1 - \frac{1}{e^{-s} + 1}\right)}^{c_n}}{{\left(1 - \frac{1}{e^{-t} + 1}\right)}^{c_n}} \cdot \color{blue}{e^{\log \left(\frac{1}{e^{-s} + 1}\right) \cdot c_p - \log \left({\left(\frac{1}{e^{-t} + 1}\right)}^{c_p}\right)}}\]
  7. Applied add-exp-log3.8

    \[\leadsto \frac{{\left(1 - \frac{1}{e^{-s} + 1}\right)}^{c_n}}{{\color{blue}{\left(e^{\log \left(1 - \frac{1}{e^{-t} + 1}\right)}\right)}}^{c_n}} \cdot e^{\log \left(\frac{1}{e^{-s} + 1}\right) \cdot c_p - \log \left({\left(\frac{1}{e^{-t} + 1}\right)}^{c_p}\right)}\]
  8. Applied pow-exp3.8

    \[\leadsto \frac{{\left(1 - \frac{1}{e^{-s} + 1}\right)}^{c_n}}{\color{blue}{e^{\log \left(1 - \frac{1}{e^{-t} + 1}\right) \cdot c_n}}} \cdot e^{\log \left(\frac{1}{e^{-s} + 1}\right) \cdot c_p - \log \left({\left(\frac{1}{e^{-t} + 1}\right)}^{c_p}\right)}\]
  9. Applied add-exp-log3.8

    \[\leadsto \frac{\color{blue}{e^{\log \left({\left(1 - \frac{1}{e^{-s} + 1}\right)}^{c_n}\right)}}}{e^{\log \left(1 - \frac{1}{e^{-t} + 1}\right) \cdot c_n}} \cdot e^{\log \left(\frac{1}{e^{-s} + 1}\right) \cdot c_p - \log \left({\left(\frac{1}{e^{-t} + 1}\right)}^{c_p}\right)}\]
  10. Applied div-exp3.6

    \[\leadsto \color{blue}{e^{\log \left({\left(1 - \frac{1}{e^{-s} + 1}\right)}^{c_n}\right) - \log \left(1 - \frac{1}{e^{-t} + 1}\right) \cdot c_n}} \cdot e^{\log \left(\frac{1}{e^{-s} + 1}\right) \cdot c_p - \log \left({\left(\frac{1}{e^{-t} + 1}\right)}^{c_p}\right)}\]
  11. Applied prod-exp3.3

    \[\leadsto \color{blue}{e^{\left(\log \left({\left(1 - \frac{1}{e^{-s} + 1}\right)}^{c_n}\right) - \log \left(1 - \frac{1}{e^{-t} + 1}\right) \cdot c_n\right) + \left(\log \left(\frac{1}{e^{-s} + 1}\right) \cdot c_p - \log \left({\left(\frac{1}{e^{-t} + 1}\right)}^{c_p}\right)\right)}}\]
  12. Simplified1.7

    \[\leadsto e^{\color{blue}{c_n \cdot \left(\log \left(1 - \frac{1}{e^{-s} + 1}\right) - \log \left(1 - \frac{1}{e^{-t} + 1}\right)\right) + \left(\log \left(e^{-t} + 1\right) - \log \left(e^{-s} + 1\right)\right) \cdot c_p}}\]
  13. Taylor expanded around 0 0.6

    \[\leadsto e^{c_n \cdot \left(\log \left(1 - \frac{1}{e^{-s} + 1}\right) - \log \left(1 - \frac{1}{e^{-t} + 1}\right)\right) + \left(\color{blue}{\left(\left(\log 2 + \frac{1}{8} \cdot {t}^{2}\right) - \frac{1}{2} \cdot t\right)} - \log \left(e^{-s} + 1\right)\right) \cdot c_p}\]
  14. Final simplification0.6

    \[\leadsto e^{c_p \cdot \left(\left(\left(\frac{1}{8} \cdot {t}^{2} + \log 2\right) - t \cdot \frac{1}{2}\right) - \log \left(1 + e^{-s}\right)\right) + c_n \cdot \left(\log \left(1 - \frac{1}{1 + e^{-s}}\right) - \log \left(1 - \frac{1}{e^{-t} + 1}\right)\right)}\]

Runtime

Time bar (total: 2.1m)Debug logProfile

BaselineHerbieOracleSpan%
Regimes0.60.60.20.40%
herbie shell --seed 2018274 
(FPCore (c_p c_n t s)
  :name "Harley's example"
  :pre (and (< 0 c_p) (< 0 c_n))

  :herbie-target
  (* (pow (/ (+ 1 (exp (- t))) (+ 1 (exp (- s)))) c_p) (pow (/ (+ 1 (exp t)) (+ 1 (exp s))) c_n))

  (/ (* (pow (/ 1 (+ 1 (exp (- s)))) c_p) (pow (- 1 (/ 1 (+ 1 (exp (- s))))) c_n)) (* (pow (/ 1 (+ 1 (exp (- t)))) c_p) (pow (- 1 (/ 1 (+ 1 (exp (- t))))) c_n))))