?

Average Error: 0.02% → 0.02%
Time: 3.1s
Precision: binary64
Cost: 6912

?

\[2 \cdot \left(x \cdot x - x \cdot y\right) \]
\[2 \cdot \mathsf{fma}\left(-y, x, x \cdot x\right) \]
(FPCore (x y) :precision binary64 (* 2.0 (- (* x x) (* x y))))
(FPCore (x y) :precision binary64 (* 2.0 (fma (- y) x (* x x))))
double code(double x, double y) {
	return 2.0 * ((x * x) - (x * y));
}
double code(double x, double y) {
	return 2.0 * fma(-y, x, (x * x));
}
function code(x, y)
	return Float64(2.0 * Float64(Float64(x * x) - Float64(x * y)))
end
function code(x, y)
	return Float64(2.0 * fma(Float64(-y), x, Float64(x * x)))
end
code[x_, y_] := N[(2.0 * N[(N[(x * x), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_, y_] := N[(2.0 * N[((-y) * x + N[(x * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
2 \cdot \left(x \cdot x - x \cdot y\right)
2 \cdot \mathsf{fma}\left(-y, x, x \cdot x\right)

Error?

Target

Original0.02%
Target0.02%
Herbie0.02%
\[\left(x \cdot 2\right) \cdot \left(x - y\right) \]

Derivation?

  1. Initial program 0.02

    \[2 \cdot \left(x \cdot x - x \cdot y\right) \]
  2. Applied egg-rr0.02

    \[\leadsto 2 \cdot \color{blue}{\left(x \cdot \left(-y\right) + \left(x \cdot x + \mathsf{fma}\left(-x, y, x \cdot y\right)\right)\right)} \]
  3. Taylor expanded in x around 0 0.05

    \[\leadsto \color{blue}{2 \cdot {x}^{2} + 2 \cdot \left(\left(-2 \cdot y + y\right) \cdot x\right)} \]
  4. Simplified0.02

    \[\leadsto \color{blue}{2 \cdot \mathsf{fma}\left(-y, x, x \cdot x\right)} \]
    Proof

    [Start]0.05

    \[ 2 \cdot {x}^{2} + 2 \cdot \left(\left(-2 \cdot y + y\right) \cdot x\right) \]

    distribute-lft-out [=>]0.05

    \[ \color{blue}{2 \cdot \left({x}^{2} + \left(-2 \cdot y + y\right) \cdot x\right)} \]

    +-commutative [<=]0.05

    \[ 2 \cdot \color{blue}{\left(\left(-2 \cdot y + y\right) \cdot x + {x}^{2}\right)} \]

    distribute-lft1-in [=>]0.03

    \[ 2 \cdot \left(\color{blue}{\left(\left(-2 + 1\right) \cdot y\right)} \cdot x + {x}^{2}\right) \]

    metadata-eval [=>]0.03

    \[ 2 \cdot \left(\left(\color{blue}{-1} \cdot y\right) \cdot x + {x}^{2}\right) \]

    fma-def [=>]0.02

    \[ 2 \cdot \color{blue}{\mathsf{fma}\left(-1 \cdot y, x, {x}^{2}\right)} \]

    mul-1-neg [=>]0.02

    \[ 2 \cdot \mathsf{fma}\left(\color{blue}{-y}, x, {x}^{2}\right) \]

    unpow2 [=>]0.02

    \[ 2 \cdot \mathsf{fma}\left(-y, x, \color{blue}{x \cdot x}\right) \]
  5. Final simplification0.02

    \[\leadsto 2 \cdot \mathsf{fma}\left(-y, x, x \cdot x\right) \]

Alternatives

Alternative 1
Error13.25%
Cost585
\[\begin{array}{l} \mathbf{if}\;y \leq -310000 \lor \neg \left(y \leq 4.8 \cdot 10^{-44}\right):\\ \;\;\;\;x \cdot \left(y \cdot -2\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(2 \cdot x\right)\\ \end{array} \]
Alternative 2
Error0.02%
Cost448
\[\left(x - y\right) \cdot \left(2 \cdot x\right) \]
Alternative 3
Error34.35%
Cost320
\[x \cdot \left(y \cdot -2\right) \]

Error

Reproduce?

herbie shell --seed 2023090 
(FPCore (x y)
  :name "Linear.Matrix:fromQuaternion from linear-1.19.1.3, A"
  :precision binary64

  :herbie-target
  (* (* x 2.0) (- x y))

  (* 2.0 (- (* x x) (* x y))))