Average Error: 0.6 → 1.0
Time: 3.8s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - \frac{\frac{1}{\frac{y - z}{x}}}{y - t}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - \frac{\frac{1}{\frac{y - z}{x}}}{y - t}
double code(double x, double y, double z, double t) {
	return ((double) (1.0 - ((double) (x / ((double) (((double) (y - z)) * ((double) (y - t))))))));
}
↓
double code(double x, double y, double z, double t) {
	return ((double) (1.0 - ((double) (((double) (1.0 / ((double) (((double) (y - z)) / x)))) / ((double) (y - t))))));
}

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 associate-/r*1.0

    \[\leadsto 1 - \color{blue}{\frac{\frac{x}{y - z}}{y - t}}\]
  4. Using strategy rm

  5. Applied clear-num1.0

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

  6. Final simplification1.0

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

Reproduce

herbie shell --seed 2020114 +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)))))