_multiplyComplex, imaginary part

?

Percentage Accurate: 99.2% → 99.7%
Time: 1.6s
Precision: binary64
Cost: 6720

?

\[x.re \cdot y.im + x.im \cdot y.re \]
\[\mathsf{fma}\left(x.re, y.im, x.im \cdot y.re\right) \]
(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (+ (* x.re y.im) (* x.im y.re)))
(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (fma x.re y.im (* x.im y.re)))
double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return (x_46_re * y_46_im) + (x_46_im * y_46_re);
}
double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return fma(x_46_re, y_46_im, (x_46_im * y_46_re));
}
function code(x_46_re, x_46_im, y_46_re, y_46_im)
	return Float64(Float64(x_46_re * y_46_im) + Float64(x_46_im * y_46_re))
end
function code(x_46_re, x_46_im, y_46_re, y_46_im)
	return fma(x_46_re, y_46_im, Float64(x_46_im * y_46_re))
end
code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := N[(N[(x$46$re * y$46$im), $MachinePrecision] + N[(x$46$im * y$46$re), $MachinePrecision]), $MachinePrecision]
code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := N[(x$46$re * y$46$im + N[(x$46$im * y$46$re), $MachinePrecision]), $MachinePrecision]
x.re \cdot y.im + x.im \cdot y.re
\mathsf{fma}\left(x.re, y.im, x.im \cdot y.re\right)

Local Percentage Accuracy?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Derivation?

  1. Initial program 99.2%

    \[x.re \cdot y.im + x.im \cdot y.re \]
  2. Simplified99.2%

    \[\leadsto \color{blue}{\mathsf{fma}\left(x.re, y.im, x.im \cdot y.re\right)} \]
    Step-by-step derivation

    [Start]99.2

    \[ x.re \cdot y.im + x.im \cdot y.re \]

    fma-def [=>]99.2

    \[ \color{blue}{\mathsf{fma}\left(x.re, y.im, x.im \cdot y.re\right)} \]
  3. Final simplification99.2%

    \[\leadsto \mathsf{fma}\left(x.re, y.im, x.im \cdot y.re\right) \]

Alternatives

Alternative 1
Accuracy74.6%
Cost712
\[\begin{array}{l} \mathbf{if}\;x.re \cdot y.im \leq -3.8 \cdot 10^{-113}:\\ \;\;\;\;x.re \cdot y.im\\ \mathbf{elif}\;x.re \cdot y.im \leq 720000:\\ \;\;\;\;x.im \cdot y.re\\ \mathbf{else}:\\ \;\;\;\;x.re \cdot y.im\\ \end{array} \]
Alternative 2
Accuracy99.2%
Cost448
\[x.im \cdot y.re + x.re \cdot y.im \]
Alternative 3
Accuracy51.6%
Cost192
\[x.re \cdot y.im \]

Error

Reproduce?

herbie shell --seed 2023160 
(FPCore (x.re x.im y.re y.im)
  :name "_multiplyComplex, imaginary part"
  :precision binary64
  (+ (* x.re y.im) (* x.im y.re)))