Average Error: 0.0 → 0.0
Time: 1.8s
Precision: binary64
\[200 \cdot \left(x - y\right) \]
↓
\[\mathsf{fma}\left(200, x, -200 \cdot y\right) \]
(FPCore (x y) :precision binary64 (* 200.0 (- x y)))
↓
(FPCore (x y) :precision binary64 (fma 200.0 x (* -200.0 y)))
double code(double x, double y) {
	return 200.0 * (x - y);
}
↓
double code(double x, double y) {
	return fma(200.0, x, (-200.0 * y));
}

function code(x, y)
	return Float64(200.0 * Float64(x - y))
end
↓
function code(x, y)
	return fma(200.0, x, Float64(-200.0 * y))
end

code[x_, y_] := N[(200.0 * N[(x - y), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_] := N[(200.0 * x + N[(-200.0 * y), $MachinePrecision]), $MachinePrecision]

200 \cdot \left(x - y\right)
↓
\mathsf{fma}\left(200, x, -200 \cdot y\right)

Error

Bits error versus x

Bits error versus y

Derivation

  1. Initial program 0.0

    \[200 \cdot \left(x - y\right) \]

  2. Taylor expanded in x around 0 0.0

    \[\leadsto \color{blue}{200 \cdot x - 200 \cdot y} \]

  3. Applied fma-neg_binary640.0

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

  4. Simplified0.0

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

  5. Final simplification0.0

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

Reproduce

herbie shell --seed 2022131 
(FPCore (x y)
  :name "Data.Colour.CIE:cieLABView from colour-2.3.3, C"
  :precision binary64
  (* 200.0 (- x y)))