[Numpy-discussion] PyTables, array and recarray

[Hanno Klemm]

Francesc, Pierre,

thanks for your replies, the view works fine. The reason why I like
recarrays is that you can address your fields simply with a.Name, when
a is your array. I find that highly convenient when working with data
interactively.

As far as I know there is no similar possbility to do that with
ndarrays, or is there?

Cheers,
Hanno

Francesc Alted <falted at pytables.org> said:

> A Friday 30 May 2008, Hanno Klemm escrigué:
> > Hi,
> >
> > I try to save the contents of a numpy recarray with PyTables into a
> > file. That works well, however, if I then try to retrieve the data, I
> > get back an array with matching dtypes rather than a recarray.
> >
> > What is the best way to get a recarray back, or if that's not
> > possible what's the most efficient way to convert an array to a
> > recarray?
> >
> > This is what I am doing at the moment:
> >
> > Python 2.5 (r25:51908, Oct  4 2006, 17:28:51)
> > [GCC 3.2.3 20030502 (Red Hat Linux 3.2.3-52)] on linux2
> > Type "help", "copyright", "credits" or "license" for more
> > information.
> >
> > >>> import numpy as N
> > >>> import tables as t
> > >>> num = 2
> > >>> a = N.recarray(num, formats='i4,f8,f8',names='id,x,y')
> > >>> a['id'] = [3,4]
> > >>> a['x'] = [3.4,4.5]
> > >>> a['y'] = [4.6,4.5]
> > >>> a
> >
> > recarray([(3, 3.3999999999999999, 4.5999999999999996), (4, 4.5,
> > 4.5)], dtype=[('id', '<i4'), ('x', '<f8'), ('y', '<f8')])
> >
> > >>> f = t.openFile('test.h5', 'w')
> > >>> f.createTable('/', 'test', a)
> >
> > /test (Table(2L,)) ''
> >   description := {
> >   "id": Int32Col(shape=(), dflt=0, pos=0),
> >   "x": Float64Col(shape=(), dflt=0.0, pos=1),
> >   "y": Float64Col(shape=(), dflt=0.0, pos=2)}
> >   byteorder := 'little'
> >   chunkshape := (409,)
> >
> > >>> f.close()
> > >>> f = t.openFile('test.h5', 'r')
> > >>> b = f.root.test[:]
> > >>> b
> >
> > array([(3, 3.3999999999999999, 4.5999999999999996), (4, 4.5, 4.5)],
> >       dtype=[('id', '<i4'), ('x', '<f8'), ('y', '<f8')])
> >
> > >>> type(b)
> >
> > <type 'numpy.ndarray'>
> >
> > >>> type(a)
> >
> > <class 'numpy.core.records.recarray'>
> 
> Yeah, this is on purpose because ndarray classes are actually C 
> extensions and they are generally more efficient than Python classes.  
> 
> If what you want is a recarray class (Python class), you can always 
> create a view as Pierre suggested.  However, this is rarely needed 
> because you can access most of the recarray functionality out of the 
> ndarray class.
> 
> Cheers,
> 
> -- 
> Francesc Alted
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> 



-- 
Hanno Klemm
klemm at phys.ethz.ch