?

Average Accuracy: 100.0% → 100.0%
Time: 6.2s
Precision: binary64
Cost: 6720

?

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

Error?

Target

Original100.0%
Target100.0%
Herbie100.0%
\[z - \left(z - x\right) \cdot y \]

Derivation?

  1. Initial program 100.0%

    \[x \cdot y + z \cdot \left(1 - y\right) \]
  2. Simplified100.0%

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

    [Start]100.0

    \[ x \cdot y + z \cdot \left(1 - y\right) \]

    +-commutative [=>]100.0

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

    sub-neg [=>]100.0

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

    distribute-rgt-in [=>]100.0

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

    associate-+l+ [=>]100.0

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

    *-lft-identity [=>]100.0

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

    +-commutative [=>]100.0

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

    *-commutative [=>]100.0

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

    neg-mul-1 [=>]100.0

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

    associate-*r* [=>]100.0

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

    distribute-rgt-out [=>]100.0

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

    fma-def [=>]100.0

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

    +-commutative [=>]100.0

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

    *-commutative [=>]100.0

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

    metadata-eval [<=]100.0

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

    cancel-sign-sub-inv [<=]100.0

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

    *-lft-identity [=>]100.0

    \[ \mathsf{fma}\left(y, x - \color{blue}{z}, z\right) \]
  3. Final simplification100.0%

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

Alternatives

Alternative 1
Accuracy63.8%
Cost917
\[\begin{array}{l} \mathbf{if}\;y \leq -9.2 \cdot 10^{-42}:\\ \;\;\;\;y \cdot x\\ \mathbf{elif}\;y \leq 5.5 \cdot 10^{-20}:\\ \;\;\;\;z\\ \mathbf{elif}\;y \leq 5.7 \cdot 10^{+35} \lor \neg \left(y \leq 2.2 \cdot 10^{+155}\right) \land y \leq 1.65 \cdot 10^{+186}:\\ \;\;\;\;y \cdot x\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(-z\right)\\ \end{array} \]
Alternative 2
Accuracy81.5%
Cost585
\[\begin{array}{l} \mathbf{if}\;y \leq -2.6 \cdot 10^{-42} \lor \neg \left(y \leq 6.8 \cdot 10^{-15}\right):\\ \;\;\;\;y \cdot \left(x - z\right)\\ \mathbf{else}:\\ \;\;\;\;z\\ \end{array} \]
Alternative 3
Accuracy81.6%
Cost585
\[\begin{array}{l} \mathbf{if}\;y \leq -4.8 \cdot 10^{-42} \lor \neg \left(y \leq 70\right):\\ \;\;\;\;y \cdot \left(x - z\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(1 - y\right)\\ \end{array} \]
Alternative 4
Accuracy98.5%
Cost585
\[\begin{array}{l} \mathbf{if}\;y \leq -1 \lor \neg \left(y \leq 1\right):\\ \;\;\;\;y \cdot \left(x - z\right)\\ \mathbf{else}:\\ \;\;\;\;z + y \cdot x\\ \end{array} \]
Alternative 5
Accuracy100.0%
Cost576
\[z \cdot \left(1 - y\right) + y \cdot x \]
Alternative 6
Accuracy63.4%
Cost456
\[\begin{array}{l} \mathbf{if}\;y \leq -9.2 \cdot 10^{-42}:\\ \;\;\;\;y \cdot x\\ \mathbf{elif}\;y \leq 6.6 \cdot 10^{-15}:\\ \;\;\;\;z\\ \mathbf{else}:\\ \;\;\;\;y \cdot x\\ \end{array} \]
Alternative 7
Accuracy100.0%
Cost448
\[z + y \cdot \left(x - z\right) \]
Alternative 8
Accuracy46.1%
Cost64
\[z \]

Error

Reproduce?

herbie shell --seed 2023133 
(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))))