Average Error: 39.6 → 0.0
Time: 1.6s
Precision: binary64
\[\frac{e^{x} - 1}{x} \]
↓
\[\frac{\mathsf{expm1}\left(x\right)}{x} \]
\frac{e^{x} - 1}{x}
↓
\frac{\mathsf{expm1}\left(x\right)}{x}

(FPCore (x) :precision binary64 (/ (- (exp x) 1.0) x))
↓
(FPCore (x) :precision binary64 (/ (expm1 x) x))
double code(double x) {
	return (exp(x) - 1.0) / x;
}
↓
double code(double x) {
	return expm1(x) / x;
}

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original39.6
Target40.1
Herbie0.0
\[\begin{array}{l} \mathbf{if}\;x < 1 \land x > -1:\\ \;\;\;\;\frac{e^{x} - 1}{\log \left(e^{x}\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{e^{x} - 1}{x}\\ \end{array} \]

Derivation

  1. Initial program 39.6

    \[\frac{e^{x} - 1}{x} \]

  2. Simplified0.0

    \[\leadsto \color{blue}{\frac{\mathsf{expm1}\left(x\right)}{x}} \]

  3. Final simplification0.0

    \[\leadsto \frac{\mathsf{expm1}\left(x\right)}{x} \]

Reproduce

herbie shell --seed 2021352 
(FPCore (x)
  :name "Kahan's exp quotient"
  :precision binary64

  :herbie-target
  (if (and (< x 1.0) (> x -1.0)) (/ (- (exp x) 1.0) (log (exp x))) (/ (- (exp x) 1.0) x))

  (/ (- (exp x) 1.0) x))