Average Error: 0.6 → 1.0
Time: 15.1s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - \frac{1}{y - z} \cdot \frac{x}{y - t}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - \frac{1}{y - z} \cdot \frac{x}{y - t}
double f(double x, double y, double z, double t) {
        double r232317 = 1.0;
        double r232318 = x;
        double r232319 = y;
        double r232320 = z;
        double r232321 = r232319 - r232320;
        double r232322 = t;
        double r232323 = r232319 - r232322;
        double r232324 = r232321 * r232323;
        double r232325 = r232318 / r232324;
        double r232326 = r232317 - r232325;
        return r232326;
}
↓
double f(double x, double y, double z, double t) {
        double r232327 = 1.0;
        double r232328 = 1.0;
        double r232329 = y;
        double r232330 = z;
        double r232331 = r232329 - r232330;
        double r232332 = r232328 / r232331;
        double r232333 = x;
        double r232334 = t;
        double r232335 = r232329 - r232334;
        double r232336 = r232333 / r232335;
        double r232337 = r232332 * r232336;
        double r232338 = r232327 - r232337;
        return r232338;
}

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 0.6

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

  3. Applied *-un-lft-identity0.6

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

  4. Applied times-frac1.0

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

  5. Final simplification1.0

    \[\leadsto 1 - \frac{1}{y - z} \cdot \frac{x}{y - t}\]

Reproduce

herbie shell --seed 2019323 
(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)))))