Average Error: 0.7 → 0.7
Time: 11.4s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - \frac{1}{\frac{\left(y - z\right) \cdot \left(y - t\right)}{x}}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - \frac{1}{\frac{\left(y - z\right) \cdot \left(y - t\right)}{x}}
double f(double x, double y, double z, double t) {
        double r241953 = 1.0;
        double r241954 = x;
        double r241955 = y;
        double r241956 = z;
        double r241957 = r241955 - r241956;
        double r241958 = t;
        double r241959 = r241955 - r241958;
        double r241960 = r241957 * r241959;
        double r241961 = r241954 / r241960;
        double r241962 = r241953 - r241961;
        return r241962;
}
↓
double f(double x, double y, double z, double t) {
        double r241963 = 1.0;
        double r241964 = 1.0;
        double r241965 = y;
        double r241966 = z;
        double r241967 = r241965 - r241966;
        double r241968 = t;
        double r241969 = r241965 - r241968;
        double r241970 = r241967 * r241969;
        double r241971 = x;
        double r241972 = r241970 / r241971;
        double r241973 = r241964 / r241972;
        double r241974 = r241963 - r241973;
        return r241974;
}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Bits error versus t

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.7

    \[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
  2. Using strategy rm

  3. Applied clear-num0.7

    \[\leadsto 1 - \color{blue}{\frac{1}{\frac{\left(y - z\right) \cdot \left(y - t\right)}{x}}}\]

  4. Final simplification0.7

    \[\leadsto 1 - \frac{1}{\frac{\left(y - z\right) \cdot \left(y - t\right)}{x}}\]

Reproduce

herbie shell --seed 2020042 +o rules:numerics
(FPCore (x y z t)
  :name "Data.Random.Distribution.Triangular:triangularCDF from random-fu-0.2.6.2, A"
  :precision binary64
  (- 1 (/ x (* (- y z) (- y t)))))