A Friday 02 May 2008, Glenn escrigué:
> Hello,
> I would like to use pytables to store the output from a spectrometer.
> The spectra come in at a rapid rate. I am having trouble
> understanding how to set up a data structure for the data. The two
> options that seem reasonable are an EArray and a Table. The example
> shown for an EArray leaves me wondering how to make an array of
> numpy 1D array rows that I can dynamically add to.
If all the data you want to save is homogeneous, using an EArray is ok.
See below an example of use:
N = 10 # your 1D array length
f = tables.openFile("test.h5", "w")
e = f.createEArray(f.root, 'earray', tables.FloatAtom(), (0,N), 'test')
for i in xrange(10):
e.append([numpy.random.rand(N)])
f.close()
> With a Table, I
> tried setting up an IsDescription subclass but could not figure out
> how to add a member to again represent a 1D array.
Generally speaking, a Table is best for saving heterogeneous datasets.
In addition, the I/O is buffered in PyTables space (and not only in
HDF5) and it is generally faster than using an EArray, so it may be
more adequate in your case.
Representing a 1D column is as easy as passing a 'shape=(N,)' argument
to your 1D columns. Look at this example:
N = 10 # your 1D array length
class TTable(tables.IsDescription):
col1 = tables.Int32Col(pos=0)
col2 = tables.Float64Col(shape=(N,), pos=1) # you 1D column
f = tables.openFile("test.h5", "w")
t = f.createTable(f.root, 'table', TTable, 'table test')
for i in xrange(10):
t.append([[i, numpy.random.rand(N)]])
t.flush()
f.close()
Hope that helps,
--
Francesc Alted
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