Vince Fulco (el 2007-11-05 a les 13:33:09 -0500) va dir::
> A bit off track from the core app but I wondered if anyone might have
> a suggestion for the best way to store (and access) a set of
> conditions to be used against an automated table query process.
>[...]
> Condition #1, temperature > 10
I would love to, but am having trouble isolating the source of the problem;
that's why my post was so vague. Unfortunately I can't really send you the
full script either because the dataset won't be put in the public domain for
a while. I'll try the earlier version of hdf5 as suggested earlier.
An
Not sure I quite understand your problem, but what about a python
dictionary of condition strings which are then pulled out and used
with eval()
I do this all the time - saves big-'switch' /multiple 'for' statements.
David
On 06/11/2007, at 5:33 AM, Vince Fulco wrote:
> A bit off track from
> Anand Patil (el 2007-10-31 a les 17:53:17 -0700) va dir::
>
> > I have a file full of 32-bit floats, in binary format, compressed with
> zip.
> > I'd like to get it into a PyTables array, but this:
> >
> > Z = ZipFile('data_file.zip')
> > binary_data = Z.read('data_file')
> > numpy_ar
A bit off track from the core app but I wondered if anyone might have
a suggestion for the best way to store (and access) a set of
conditions to be used against an automated table query process. Not
sure if the easiest and most efficient way is to store in a text file
and then use line splits to b
