Average Error: 0.2 → 0.2
Time: 3.3s
Precision: 64
\[0.0 \lt m \land 0.0 \lt v \land v \lt 0.25\]
\[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m\]
↓
\[\left(\frac{1}{\frac{v}{m \cdot \left(1 - m\right)}} - 1\right) \cdot m\]
\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m
↓
\left(\frac{1}{\frac{v}{m \cdot \left(1 - m\right)}} - 1\right) \cdot m
double f(double m, double v) {
        double r8915 = m;
        double r8916 = 1.0;
        double r8917 = r8916 - r8915;
        double r8918 = r8915 * r8917;
        double r8919 = v;
        double r8920 = r8918 / r8919;
        double r8921 = r8920 - r8916;
        double r8922 = r8921 * r8915;
        return r8922;
}
↓
double f(double m, double v) {
        double r8923 = 1.0;
        double r8924 = v;
        double r8925 = m;
        double r8926 = 1.0;
        double r8927 = r8926 - r8925;
        double r8928 = r8925 * r8927;
        double r8929 = r8924 / r8928;
        double r8930 = r8923 / r8929;
        double r8931 = r8930 - r8926;
        double r8932 = r8931 * r8925;
        return r8932;
}

Error

Bits error versus m

Bits error versus v

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.2

    \[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m\]
  2. Using strategy rm

  3. Applied clear-num0.2

    \[\leadsto \left(\color{blue}{\frac{1}{\frac{v}{m \cdot \left(1 - m\right)}}} - 1\right) \cdot m\]

  4. Final simplification0.2

    \[\leadsto \left(\frac{1}{\frac{v}{m \cdot \left(1 - m\right)}} - 1\right) \cdot m\]

Reproduce

herbie shell --seed 2020062 +o rules:numerics
(FPCore (m v)
  :name "a parameter of renormalized beta distribution"
  :precision binary64
  :pre (and (< 0.0 m) (< 0.0 v) (< v 0.25))
  (* (- (/ (* m (- 1 m)) v) 1) m))