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 wrote:
> import time
> import numpy as np
>
> dtype = np.format_parser(['i4', 'i4'], [], [])
> N
That is reason enough for me really. If someone really wants a recarray,
they could always convert an ndarray to this. I think it is still worth
asking the numpy list what the status is...
Be Well
Anthony
On Thu, Jun 28, 2012 at 4:13 PM, Josh Ayers wrote:
> There is a big difference in speed
There is a big difference in speed when iterating over the rows. Possibly
that was the reason structured arrays were chosen? The issue is mentioned
here: http://www.scipy.org/Cookbook/Recarray
In a simple test, I get a difference of about 15x, so it is significant.
Iterating over a recarray with
On Thu, Jun 28, 2012 at 3:23 PM, Francesc Alted 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 exactly the argu
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 arra
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 wrote:
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 wrote:
> Hi Alvaro,
>
> I think
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 wrote:
> Hi,
>
> I've noticed that tables are loaded in memory as
Hi,
I've noticed that tables are loaded in memory as structured arrays.
It seems that returning recarrays by default would be much in the
spirit of the natural naming preferences of PyTables.
Is there a reason not to do so?
Cheers,
Álvaro.
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