Average Error: 0.7 → 0.7
Time: 3.2s
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 r198338 = 1.0;
        double r198339 = x;
        double r198340 = y;
        double r198341 = z;
        double r198342 = r198340 - r198341;
        double r198343 = t;
        double r198344 = r198340 - r198343;
        double r198345 = r198342 * r198344;
        double r198346 = r198339 / r198345;
        double r198347 = r198338 - r198346;
        return r198347;
}
↓
double f(double x, double y, double z, double t) {
        double r198348 = 1.0;
        double r198349 = 1.0;
        double r198350 = y;
        double r198351 = z;
        double r198352 = r198350 - r198351;
        double r198353 = t;
        double r198354 = r198350 - r198353;
        double r198355 = r198352 * r198354;
        double r198356 = x;
        double r198357 = r198355 / r198356;
        double r198358 = r198349 / r198357;
        double r198359 = r198348 - r198358;
        return r198359;
}

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 2020089 +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)))))