0
down vote
favorite 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 :=Truecolindexes
:={"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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