Average Error: 0.7 → 1.2
Time: 2.0s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - \frac{\frac{x}{y - t}}{y - z}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - \frac{\frac{x}{y - t}}{y - z}
double code(double x, double y, double z, double t) {
	return (1.0 - (x / ((y - z) * (y - t))));
}
↓
double code(double x, double y, double z, double t) {
	return (1.0 - ((x / (y - t)) / (y - z)));
}

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 *-commutative0.7

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

  4. Applied associate-/r*1.2

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

  5. Final simplification1.2

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

Reproduce

herbie shell --seed 2020078 +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)))))