Average Error: 0.6 → 0.7
Time: 4.5s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - x \cdot \frac{1}{\left(y - z\right) \cdot \left(y - t\right)}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - x \cdot \frac{1}{\left(y - z\right) \cdot \left(y - t\right)}
double f(double x, double y, double z, double t) {
        double r207356 = 1.0;
        double r207357 = x;
        double r207358 = y;
        double r207359 = z;
        double r207360 = r207358 - r207359;
        double r207361 = t;
        double r207362 = r207358 - r207361;
        double r207363 = r207360 * r207362;
        double r207364 = r207357 / r207363;
        double r207365 = r207356 - r207364;
        return r207365;
}
↓
double f(double x, double y, double z, double t) {
        double r207366 = 1.0;
        double r207367 = x;
        double r207368 = 1.0;
        double r207369 = y;
        double r207370 = z;
        double r207371 = r207369 - r207370;
        double r207372 = t;
        double r207373 = r207369 - r207372;
        double r207374 = r207371 * r207373;
        double r207375 = r207368 / r207374;
        double r207376 = r207367 * r207375;
        double r207377 = r207366 - r207376;
        return r207377;
}

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 div-inv0.7

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

  4. Final simplification0.7

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

Reproduce

herbie shell --seed 2020036 +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)))))