[Numpy-discussion] Correlate with small arrays

[Peter Creasey]

>  >  I'm trying to do a PDE style calculation with numpy arrays
>  >
>  >  y = a * x[:-2] + b * x[1:-1] + c * x[2:]
>  >
>  >  with a,b,c constants. I realise I could use correlate for this, i.e
>  >
>  >  y = numpy.correlate(x, array((a, b, c)))
>
>  The relative performance seems to vary depending on the size, but it
>  seems to me that correlate usually beats the manual implementation,
>  particularly if you don't measure the array() part, too. len(x)=1000
>  is the only size where the manual version seems to beat correlate on
>  my machine.

Thanks for the quick response! Unfortunately 1000 < len(x) < 20000 are
just the cases I'm using, (they seem to be 1-3 times as slower on my
machine).

I'm just thinking that this is exactly the kind of problem that could
be done much faster in C, i.e in the manual implementation the
processor goes through an array of len(x) maybe 5 times (3
multiplications and 2 additions), yet in C I could put those constants
in the registers and go through the array just once. Maybe this is
flawed logic, but if not I'm hoping someone has already done this?