Average Error: 2.0 → 2.0
Time: 1.2min
Precision: binary64
\[x + \left(y - x\right) \cdot \frac{z}{t} \]
\[\mathsf{fma}\left(y - x, \frac{z}{t}, x\right) \]
x + \left(y - x\right) \cdot \frac{z}{t}
\mathsf{fma}\left(y - x, \frac{z}{t}, x\right)
(FPCore (x y z t) :precision binary64 (+ x (* (- y x) (/ z t))))
(FPCore (x y z t) :precision binary64 (fma (- y x) (/ z t) x))
double code(double x, double y, double z, double t) {
	return x + ((y - x) * (z / t));
}
double code(double x, double y, double z, double t) {
	return fma((y - x), (z / t), x);
}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Bits error versus t

Target

Original2.0
Target2.2
Herbie2.0
\[\begin{array}{l} \mathbf{if}\;\left(y - x\right) \cdot \frac{z}{t} < -1013646692435.8867:\\ \;\;\;\;x + \frac{y - x}{\frac{t}{z}}\\ \mathbf{elif}\;\left(y - x\right) \cdot \frac{z}{t} < 0:\\ \;\;\;\;x + \frac{\left(y - x\right) \cdot z}{t}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y - x}{\frac{t}{z}}\\ \end{array} \]

Derivation

  1. Initial program 2.0

    \[x + \left(y - x\right) \cdot \frac{z}{t} \]
  2. Simplified2.0

    \[\leadsto \color{blue}{\mathsf{fma}\left(y - x, \frac{z}{t}, x\right)} \]
  3. Final simplification2.0

    \[\leadsto \mathsf{fma}\left(y - x, \frac{z}{t}, x\right) \]

Reproduce

herbie shell --seed 2022130 
(FPCore (x y z t)
  :name "Graphics.Rendering.Plot.Render.Plot.Axis:tickPosition from plot-0.2.3.4"
  :precision binary64

  :herbie-target
  (if (< (* (- y x) (/ z t)) -1013646692435.8867) (+ x (/ (- y x) (/ t z))) (if (< (* (- y x) (/ z t)) 0.0) (+ x (/ (* (- y x) z) t)) (+ x (/ (- y x) (/ t z)))))

  (+ x (* (- y x) (/ z t))))