Average Error: 0.4 → 0.1
Time: 3.6s
Precision: binary64
\[x + \left(\left(y - x\right) \cdot 6\right) \cdot \left(\frac{2}{3} - z\right) \]
↓
\[\mathsf{fma}\left(x, -3, \mathsf{fma}\left(6, \left(x - y\right) \cdot z, y \cdot 4\right)\right) \]
(FPCore (x y z)
 :precision binary64
 (+ x (* (* (- y x) 6.0) (- (/ 2.0 3.0) z))))
↓
(FPCore (x y z)
 :precision binary64
 (fma x -3.0 (fma 6.0 (* (- x y) z) (* y 4.0))))
double code(double x, double y, double z) {
	return x + (((y - x) * 6.0) * ((2.0 / 3.0) - z));
}
↓
double code(double x, double y, double z) {
	return fma(x, -3.0, fma(6.0, ((x - y) * z), (y * 4.0)));
}

function code(x, y, z)
	return Float64(x + Float64(Float64(Float64(y - x) * 6.0) * Float64(Float64(2.0 / 3.0) - z)))
end
↓
function code(x, y, z)
	return fma(x, -3.0, fma(6.0, Float64(Float64(x - y) * z), Float64(y * 4.0)))
end

code[x_, y_, z_] := N[(x + N[(N[(N[(y - x), $MachinePrecision] * 6.0), $MachinePrecision] * N[(N[(2.0 / 3.0), $MachinePrecision] - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_] := N[(x * -3.0 + N[(6.0 * N[(N[(x - y), $MachinePrecision] * z), $MachinePrecision] + N[(y * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

x + \left(\left(y - x\right) \cdot 6\right) \cdot \left(\frac{2}{3} - z\right)
↓
\mathsf{fma}\left(x, -3, \mathsf{fma}\left(6, \left(x - y\right) \cdot z, y \cdot 4\right)\right)

Error

Bits error versus x

Bits error versus y

Bits error versus z

Derivation

  1. Initial program 0.4

    \[x + \left(\left(y - x\right) \cdot 6\right) \cdot \left(\frac{2}{3} - z\right) \]

  2. Simplified0.2

    \[\leadsto \color{blue}{\mathsf{fma}\left(y - x, \mathsf{fma}\left(z, -6, 4\right), x\right)} \]

  3. Taylor expanded in y around 0 0.2

    \[\leadsto \color{blue}{\left(4 \cdot y + 6 \cdot \left(z \cdot x\right)\right) - \left(6 \cdot \left(y \cdot z\right) + 3 \cdot x\right)} \]

  4. Applied associate--r+_binary640.2

    \[\leadsto \color{blue}{\left(\left(4 \cdot y + 6 \cdot \left(z \cdot x\right)\right) - 6 \cdot \left(y \cdot z\right)\right) - 3 \cdot x} \]

  5. Simplified0.2

    \[\leadsto \color{blue}{\mathsf{fma}\left(y, 4, 6 \cdot \left(z \cdot \left(x - y\right)\right)\right)} - 3 \cdot x \]

  6. Taylor expanded in y around 0 0.2

    \[\leadsto \color{blue}{\left(4 \cdot y + 6 \cdot \left(z \cdot x\right)\right) - \left(6 \cdot \left(y \cdot z\right) + 3 \cdot x\right)} \]

  7. Simplified0.1

    \[\leadsto \color{blue}{\mathsf{fma}\left(x, -3, \mathsf{fma}\left(6, z \cdot \left(x - y\right), y \cdot 4\right)\right)} \]

  8. Taylor expanded in z around 0 0.1

    \[\leadsto \mathsf{fma}\left(x, -3, \mathsf{fma}\left(6, \color{blue}{\left(x - y\right) \cdot z}, y \cdot 4\right)\right) \]

  9. Final simplification0.1

    \[\leadsto \mathsf{fma}\left(x, -3, \mathsf{fma}\left(6, \left(x - y\right) \cdot z, y \cdot 4\right)\right) \]

Reproduce

herbie shell --seed 2022131 
(FPCore (x y z)
  :name "Data.Colour.RGBSpace.HSL:hsl from colour-2.3.3, D"
  :precision binary64
  (+ x (* (* (- y x) 6.0) (- (/ 2.0 3.0) z))))