Average Error: 0.0 → 0.0
Time: 1.9s
Precision: binary64
\[\frac{2}{e^{x} + e^{-x}}\]
↓
\[0.5 \cdot \frac{2}{\cosh x}\]
\frac{2}{e^{x} + e^{-x}}
↓
0.5 \cdot \frac{2}{\cosh x}
(FPCore (x) :precision binary64 (/ 2.0 (+ (exp x) (exp (- x)))))
↓
(FPCore (x) :precision binary64 (* 0.5 (/ 2.0 (cosh x))))
double code(double x) {
	return 2.0 / (exp(x) + exp(-x));
}
↓
double code(double x) {
	return 0.5 * (2.0 / cosh(x));
}

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.0

    \[\frac{2}{e^{x} + e^{-x}}\]
  2. Using strategy rm

  3. Applied cosh-undef_binary64_19770.0

    \[\leadsto \frac{2}{\color{blue}{2 \cdot \cosh x}}\]

  4. Applied *-un-lft-identity_binary64_17830.0

    \[\leadsto \frac{\color{blue}{1 \cdot 2}}{2 \cdot \cosh x}\]

  5. Applied times-frac_binary64_17890.0

    \[\leadsto \color{blue}{\frac{1}{2} \cdot \frac{2}{\cosh x}}\]

  6. Simplified0.0

    \[\leadsto \color{blue}{0.5} \cdot \frac{2}{\cosh x}\]

  7. Final simplification0.0

    \[\leadsto 0.5 \cdot \frac{2}{\cosh x}\]

Reproduce

herbie shell --seed 2021098 
(FPCore (x)
  :name "Hyperbolic secant"
  :precision binary64
  (/ 2.0 (+ (exp x) (exp (- x)))))