Hello,
I have been using pytables for a few moths. The main structure of my files
has a four column table, two of which have multidimensional cells, (56,1)
and (133,6) respectively. The previous structure had more columns instead
of storing the 56x1 array into the same cell. The largest file has a
Hello Juan,
Try using the where() method [1], It has a lot of nice features under the
covers.
Be Well
Anthony
1.
http://pytables.github.com/usersguide/libref.html?highlight=where#tables.Table.where
On Sun, Jul 15, 2012 at 4:01 PM, Juan Manuel Vázquez Tovar <
jmv.to...@gmail.com> wrote:
> Hell
Hello Anthony,
I have to loop over the whole set of rows. Does the where method has any
advantages in that case?
Thank you,
Juanma
2012/7/15 Anthony Scopatz
> Hello Juan,
>
> Try using the where() method [1], It has a lot of nice features under the
> covers.
>
> Be Well
> Anthony
>
> 1.
> htt
Rereading the original post, I am a little confused are your trying to read
the whole table, just a couple of rows that meet some condition, or just
one whole column, or one part of the column.
To request the whole table without looping over each row in Python, index
every element:
f.root.table[:
The column I´m requesting the data from has multidimensional cells, so each
time I request data from the table, I need to get a specific row for all
the multidimensional cells in the column. I hope this clarifies a bit.
I have at the office a Linux workstation, but it is part of a computing
cluster
Ahh I see, tricky.
So I think what is killing you is that you are pulling each row of the
table individually over the network. Ideally you should be able to do
something like the following:
f.root.table.cols.my_col[:,n,:]
using numpy-esque multidimensional slicing. However, this fails when I
