Average Error: 0.7 → 0.7
Time: 7.7s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - \frac{x}{\left(y - t\right) \cdot \left(y - z\right)}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - \frac{x}{\left(y - t\right) \cdot \left(y - z\right)}
double f(double x, double y, double z, double t) {
        double r203355 = 1.0;
        double r203356 = x;
        double r203357 = y;
        double r203358 = z;
        double r203359 = r203357 - r203358;
        double r203360 = t;
        double r203361 = r203357 - r203360;
        double r203362 = r203359 * r203361;
        double r203363 = r203356 / r203362;
        double r203364 = r203355 - r203363;
        return r203364;
}
↓
double f(double x, double y, double z, double t) {
        double r203365 = 1.0;
        double r203366 = x;
        double r203367 = y;
        double r203368 = t;
        double r203369 = r203367 - r203368;
        double r203370 = z;
        double r203371 = r203367 - r203370;
        double r203372 = r203369 * r203371;
        double r203373 = r203366 / r203372;
        double r203374 = r203365 - r203373;
        return r203374;
}

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 *-un-lft-identity0.7

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

  4. Applied associate-*l*0.7

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

  5. Simplified0.7

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

  6. Final simplification0.7

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

Reproduce

herbie shell --seed 2020045 +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)))))