Average Error: 0.0 → 0.0
Time: 1.9s
Precision: binary64
\[x \cdot y + z \cdot \left(1 - y\right) \]
\[\mathsf{fma}\left(x, y, z \cdot \left(1 - y\right)\right) \]
(FPCore (x y z) :precision binary64 (+ (* x y) (* z (- 1.0 y))))
(FPCore (x y z) :precision binary64 (fma x y (* z (- 1.0 y))))
double code(double x, double y, double z) {
	return (x * y) + (z * (1.0 - y));
}
double code(double x, double y, double z) {
	return fma(x, y, (z * (1.0 - y)));
}
function code(x, y, z)
	return Float64(Float64(x * y) + Float64(z * Float64(1.0 - y)))
end
function code(x, y, z)
	return fma(x, y, Float64(z * Float64(1.0 - y)))
end
code[x_, y_, z_] := N[(N[(x * y), $MachinePrecision] + N[(z * N[(1.0 - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_, y_, z_] := N[(x * y + N[(z * N[(1.0 - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
x \cdot y + z \cdot \left(1 - y\right)
\mathsf{fma}\left(x, y, z \cdot \left(1 - y\right)\right)

Error

Bits error versus x

Bits error versus y

Bits error versus z

Target

Original0.0
Target0.0
Herbie0.0
\[z - \left(z - x\right) \cdot y \]

Derivation

  1. Initial program 0.0

    \[x \cdot y + z \cdot \left(1 - y\right) \]
  2. Applied fma-def_binary640.0

    \[\leadsto \color{blue}{\mathsf{fma}\left(x, y, z \cdot \left(1 - y\right)\right)} \]
  3. Final simplification0.0

    \[\leadsto \mathsf{fma}\left(x, y, z \cdot \left(1 - y\right)\right) \]

Reproduce

herbie shell --seed 2022131 
(FPCore (x y z)
  :name "Diagrams.TwoD.Segment:bezierClip from diagrams-lib-1.3.0.3"
  :precision binary64

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

  (+ (* x y) (* z (- 1.0 y))))