Average Error: 0.0 → 0.0
Time: 13.1s
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 r25934 = 1.0;
        double r25935 = x;
        double r25936 = r25935 * r25935;
        double r25937 = r25934 - r25936;
        double r25938 = -r25937;
        double r25939 = exp(r25938);
        return r25939;
}
↓
double f(double x) {
        double r25940 = 1.0;
        double r25941 = 1.0;
        double r25942 = x;
        double r25943 = r25942 * r25942;
        double r25944 = r25941 - r25943;
        double r25945 = exp(r25944);
        double r25946 = r25940 / r25945;
        return r25946;
}

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 2020042 
(FPCore (x)
  :name "exp neg sub"
  :precision binary64
  (exp (- (- 1 (* x x)))))