Hi Alvaro,
I think if you save the table as a record array, it should return you a
record array. Or does it return a structured array? Have you tried this?
Be Well
Anthony
On Thu, Jun 28, 2012 at 11:22 AM, Alvaro Tejero Cantero alv...@minin.eswrote:
Hi,
I've noticed that tables are loaded
I just tested: passing an object of type numpy.core.records.recarray
to the constructor of createTable and then reading back it into memory
via slicing (h5f.root.myobj[:] ) returns to me a numpy.ndarray.
Best,
-á.
On Thu, Jun 28, 2012 at 5:30 PM, Anthony Scopatz scop...@gmail.com wrote:
Hi
Hmmm Ok. Maybe there needs to be a recarray flavor.
I kind of like just returning a normal ndarray, though I see your argument
for returning a recarray. Maybe some of the other devs can jump in here
with an opinion.
Be Well
Anthony
On Thu, Jun 28, 2012 at 12:37 PM, Alvaro Tejero Cantero
Yes, I think it would make more sense to return a recarray too.
However, I remember many time ago (3, 4 years?) that NumPy developers
were recommending using structured arrays instead of recarrays. I don't
remember exactly the arguments, but I think that was the reason why the
structured
On Thu, Jun 28, 2012 at 3:23 PM, Francesc Alted fal...@pytables.org wrote:
Yes, I think it would make more sense to return a recarray too. However,
I remember many time ago (3, 4 years?) that NumPy developers were
recommending using structured arrays instead of recarrays. I don't
remember
Thank you Josh, that is representative enough. In my system the
speedup of structured arrays is ~30x. A copy of the whole array is
still ~6x faster.
-á.
On Thu, Jun 28, 2012 at 10:13 PM, Josh Ayers josh.ay...@gmail.com wrote:
import time
import numpy as np
dtype = np.format_parser(['i4',
