Average Error: 0.1 → 0.1
Time: 2.2s
Precision: binary64
\[3 \cdot \left(\left(\left(x \cdot 3\right) \cdot x - x \cdot 4\right) + 1\right) \]
↓
\[\mathsf{fma}\left(x, x \cdot 9 + -12, 3\right) \]
(FPCore (x) :precision binary64 (* 3.0 (+ (- (* (* x 3.0) x) (* x 4.0)) 1.0)))
↓
(FPCore (x) :precision binary64 (fma x (+ (* x 9.0) -12.0) 3.0))
double code(double x) {
	return 3.0 * ((((x * 3.0) * x) - (x * 4.0)) + 1.0);
}
↓
double code(double x) {
	return fma(x, ((x * 9.0) + -12.0), 3.0);
}

function code(x)
	return Float64(3.0 * Float64(Float64(Float64(Float64(x * 3.0) * x) - Float64(x * 4.0)) + 1.0))
end
↓
function code(x)
	return fma(x, Float64(Float64(x * 9.0) + -12.0), 3.0)
end

code[x_] := N[(3.0 * N[(N[(N[(N[(x * 3.0), $MachinePrecision] * x), $MachinePrecision] - N[(x * 4.0), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]
↓
code[x_] := N[(x * N[(N[(x * 9.0), $MachinePrecision] + -12.0), $MachinePrecision] + 3.0), $MachinePrecision]

3 \cdot \left(\left(\left(x \cdot 3\right) \cdot x - x \cdot 4\right) + 1\right)
↓
\mathsf{fma}\left(x, x \cdot 9 + -12, 3\right)

Error

Bits error versus x

Target

Original0.1
Target0.1
Herbie0.1
\[3 + \left(\left(9 \cdot x\right) \cdot x - 12 \cdot x\right) \]

Derivation

  1. Initial program 0.1

    \[3 \cdot \left(\left(\left(x \cdot 3\right) \cdot x - x \cdot 4\right) + 1\right) \]

  2. Simplified0.1

    \[\leadsto \color{blue}{\mathsf{fma}\left(x, \mathsf{fma}\left(x, 9, -12\right), 3\right)} \]

  3. Applied egg-rr0.1

    \[\leadsto \mathsf{fma}\left(x, \color{blue}{x \cdot 9 + -12}, 3\right) \]

  4. Final simplification0.1

    \[\leadsto \mathsf{fma}\left(x, x \cdot 9 + -12, 3\right) \]

Reproduce

herbie shell --seed 2022150 
(FPCore (x)
  :name "Diagrams.Tangent:$catParam from diagrams-lib-1.3.0.3, D"
  :precision binary64

  :herbie-target
  (+ 3.0 (- (* (* 9.0 x) x) (* 12.0 x)))

  (* 3.0 (+ (- (* (* x 3.0) x) (* x 4.0)) 1.0)))