?

Average Accuracy: 100.0% → 100.0%
Time: 5.7s
Precision: binary64
Cost: 6720

?

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

Error?

Derivation?

  1. Initial program 100.0%

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

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

    [Start]100.0

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

    +-commutative [=>]100.0

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

    fma-def [=>]100.0

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

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

Alternatives

Alternative 1
Accuracy79.5%
Cost848
\[\begin{array}{l} t_0 := y \cdot \left(z - x\right)\\ \mathbf{if}\;y \leq -1.75 \cdot 10^{-81}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y \leq 7.8 \cdot 10^{-57}:\\ \;\;\;\;x\\ \mathbf{elif}\;y \leq 9 \cdot 10^{-26}:\\ \;\;\;\;y \cdot z\\ \mathbf{elif}\;y \leq 14500000:\\ \;\;\;\;x \cdot \left(1 - y\right)\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]
Alternative 2
Accuracy61.3%
Cost784
\[\begin{array}{l} \mathbf{if}\;y \leq -5.5 \cdot 10^{-82}:\\ \;\;\;\;y \cdot z\\ \mathbf{elif}\;y \leq 4 \cdot 10^{-56}:\\ \;\;\;\;x\\ \mathbf{elif}\;y \leq 4.5 \cdot 10^{+54}:\\ \;\;\;\;y \cdot z\\ \mathbf{elif}\;y \leq 4.5 \cdot 10^{+89}:\\ \;\;\;\;x \cdot \left(-y\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot z\\ \end{array} \]
Alternative 3
Accuracy79.4%
Cost585
\[\begin{array}{l} \mathbf{if}\;y \leq -1.55 \cdot 10^{-81} \lor \neg \left(y \leq 4.2 \cdot 10^{-55}\right):\\ \;\;\;\;y \cdot \left(z - x\right)\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]
Alternative 4
Accuracy100.0%
Cost576
\[x + \left(y \cdot z - y \cdot x\right) \]
Alternative 5
Accuracy61.6%
Cost456
\[\begin{array}{l} \mathbf{if}\;y \leq -1.85 \cdot 10^{-81}:\\ \;\;\;\;y \cdot z\\ \mathbf{elif}\;y \leq 2.1 \cdot 10^{-55}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;y \cdot z\\ \end{array} \]
Alternative 6
Accuracy100.0%
Cost448
\[x + y \cdot \left(z - x\right) \]
Alternative 7
Accuracy44.6%
Cost64
\[x \]

Error

Reproduce?

herbie shell --seed 2023146 
(FPCore (x y z)
  :name "SynthBasics:oscSampleBasedAux from YampaSynth-0.2"
  :precision binary64
  (+ x (* y (- z x))))