Hi Charles,
We just discussed this last week and I am too lazy to retype it all so here
is a link to the archive post [1].
Be Well
Anthony
1. http://sourceforge.net/mailarchive/message.php?msg_id=30708089
On Mon, Apr 15, 2013 at 9:20 AM, Charles de Villiers <chas...@yahoo.com>wrote:
>
> 0down
> votefavorite<http://stackoverflow.com/questions/16013711/pytables-in-kernel-search-on-time64col#>
> **
> I'm using PyTables 2.4.0 and Python 2.7 I've got a database that contains
> the following typical table:
>
> /anc/asc_wind_speed (Table(87591,), shuffle, blosc(3)) 'Wind speed'
> description := {
> "value_seconds": Time64Col(shape=(), dflt=0.0, pos=0),
> "update_seconds": Time64Col(shape=(), dflt=0.0, pos=1),
> "status": UInt8Col(shape=(), dflt=0, pos=2),
> "value": Float64Col(shape=(), dflt=0.0, pos=3)}
> byteorder := 'little'
> chunkshape := (2621,)
> autoIndex := True
> colindexes := {
> "update_seconds": Index(9, full, shuffle, zlib(1)).is_CSI=True,
> "value": Index(9, full, shuffle, zlib(1)).is_CSI=True}
>
> I populate the timestamp columns using float seconds.
> The data looks OK in my IPython session:
>
> array([(1343779432.2160001, 1343779431.8529999, 0, 5.2975000000000003),
> (1343779433.2190001, 1343779432.9430001, 0, 5.7474999999999996),
> (1343779434.217, 1343779433.9809999, 0, 5.8600000000000003), ...,
> (1343866301.934, 1343866301.5139999, 0, 3.8424999999999998),
> (1343866302.934, 1343866302.5799999, 0, 4.0599999999999996),
> (1343866303.934, 1343866303.642, 0, 3.7825000000000002)],
>
> dtype=[('value_seconds', '<f8'), ('update_seconds', '<f8'), ('status',
> '|u1'), ('value', '<f8')])
>
> .. but when I try to do an in-kernel search using the indexed column
> 'update_seconds', everything goes pear-shaped:
>
> len(wstable.readWhere('(update_seconds <= 1343866303.642)'))0
>
> ie I get 0 rows returned when I was expecting all 87591 of them.
> Occasionally I do manage to get some rows with a '>=' query, but the
> timestamp columns are then returned as huge floats (~10^79). It seems that
> there is some implicit type-conversion going on that causes the Time64Col
> values to be misinterpreted. Can someone spot my mistake, or should I
> forget about Time64Cols and convert them all to Float64 (and how do I do
> this?)
>
>
>
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apps and a phenomenal toolset for data science. Developers can use
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