Average Error: 0.0 → 0.0
Time: 1.3s
Precision: 64
\[200 \cdot \left(x - y\right)\]
\[\mathsf{fma}\left(200, x, 200 \cdot \left(-y\right)\right)\]
200 \cdot \left(x - y\right)
\mathsf{fma}\left(200, x, 200 \cdot \left(-y\right)\right)
double f(double x, double y) {
        double r251068 = 200.0;
        double r251069 = x;
        double r251070 = y;
        double r251071 = r251069 - r251070;
        double r251072 = r251068 * r251071;
        return r251072;
}

double f(double x, double y) {
        double r251073 = 200.0;
        double r251074 = x;
        double r251075 = y;
        double r251076 = -r251075;
        double r251077 = r251073 * r251076;
        double r251078 = fma(r251073, r251074, r251077);
        return r251078;
}

Error

Bits error versus x

Bits error versus y

Derivation

  1. Initial program 0.0

    \[200 \cdot \left(x - y\right)\]
  2. Using strategy rm
  3. Applied sub-neg0.0

    \[\leadsto 200 \cdot \color{blue}{\left(x + \left(-y\right)\right)}\]
  4. Applied distribute-lft-in0.0

    \[\leadsto \color{blue}{200 \cdot x + 200 \cdot \left(-y\right)}\]
  5. Using strategy rm
  6. Applied fma-def0.0

    \[\leadsto \color{blue}{\mathsf{fma}\left(200, x, 200 \cdot \left(-y\right)\right)}\]
  7. Final simplification0.0

    \[\leadsto \mathsf{fma}\left(200, x, 200 \cdot \left(-y\right)\right)\]

Reproduce

herbie shell --seed 2020027 +o rules:numerics
(FPCore (x y)
  :name "Data.Colour.CIE:cieLABView from colour-2.3.3, C"
  :precision binary64
  (* 200 (- x y)))