Hi,
I have two tables in my dataset, a large one and a small one. The
smaller table contains (among other data) pointers to row-numbers in
the larger one. I would like to restrict the search to those rows.
This approach works:
indices =
t.root.collocs.mean_collocations.read(start=1,stop=1494,field="FIRST")
S = set(indices) # faster searching
res = (row for row in
t.root.collocs.collocations.where(condition="(B_LAT < 0)",
start=1, stop=65508)
if row.nrow in S)
However, I wonder if I can do this in-kernel somehow.
mytable[indices].where(...) doesn't work, because mytable[indices] is
a numpy.ndarray already, not a table that supports in-kernel
searching. I tried something like mytable.where("(B_LAT < 0) & (NO in
S)") (where I need to add NO explicitly to the table?), but this
results in an exception "TypeError: variable ``S`` has data type
``object``, not allowed in conditions". If I use "...NO in indices..."
instead (should be much slower) I get "TypeError: argument of type
'VariableNode' is not iterable"
Can this be done in-kernel?
I could rearrange my data in a quite different way, and rather than
have those 'pointers', use an embedded table. However, quite often I
am only interested in the larger table, and searching in this one
would become much slower. Yet another approach that would allow
in-kernel searches would be to repeat the entire row from the larger
table in the smaller table, but that would be inefficient
storage-wise.
Any hints?
Gerrit.
--
Gerrit Holl
PhD student at Department of Space Science, Luleå University of
Technology, Kiruna, Sweden
http://www.sat.ltu.se/members/gerrit/
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