Average Error: 0.0 → 0.0
Time: 6.8s
Precision: 64
\[e^{-\left(1 - x \cdot x\right)}\]
↓
\[\frac{1}{e^{1 - x \cdot x}}\]
e^{-\left(1 - x \cdot x\right)}
↓
\frac{1}{e^{1 - x \cdot x}}
double f(double x) {
        double r66904 = 1.0;
        double r66905 = x;
        double r66906 = r66905 * r66905;
        double r66907 = r66904 - r66906;
        double r66908 = -r66907;
        double r66909 = exp(r66908);
        return r66909;
}
↓
double f(double x) {
        double r66910 = 1.0;
        double r66911 = 1.0;
        double r66912 = x;
        double r66913 = r66912 * r66912;
        double r66914 = r66911 - r66913;
        double r66915 = exp(r66914);
        double r66916 = r66910 / r66915;
        return r66916;
}

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

    \[e^{-\left(1 - x \cdot x\right)}\]
  2. Using strategy rm

  3. Applied exp-neg0.0

    \[\leadsto \color{blue}{\frac{1}{e^{1 - x \cdot x}}}\]

  4. Final simplification0.0

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

Reproduce

herbie shell --seed 2019353 
(FPCore (x)
  :name "exp neg sub"
  :precision binary64
  (exp (- (- 1 (* x x)))))