Saving dictionary of header information using numpy.savez()

Question

I am trying to save an array of data along with header information. Currently, I am using numpy.savez() to save the header information (a dictionary) in one array, and the data in another.

    data = [[1,2,3],[4,5,6]]
    header = {'TIME': time, 'POSITION': position}
    np.savez(filename, header=header, data=data)

When I try to load and read the file, however, I can't index the header dictionary.

    arrays = np.load(filename)
    header = arrays('header')
    data = arrays('data')
    print header['TIME']

I get the following error:

    ValueError: field named TIME not found.

Before saving, the header is type 'dict'. After saving/loading, it is type 'numpy.ndarray'. Can I convert it back to a dictionary? Or is there a better way to achieve the same result?

Answer 1

np.savez saves only numpy arrays. If you give it a dict, it will call np.array(yourdict) before saving it. So this is why you see something like type(arrays['header']) as np.ndarray:

arrays = np.load(filename)
h = arrays['header'] # square brackets!!

>>> h
array({'POSITION': (23, 54), 'TIME': 23.5}, dtype=object)

You'll notice if you look at it though, that it is a 0-dimensional, single-item array, with one dict inside:

>>> h.shape
()
>>> h.dtype
dtype('O') # the 'object' dtype, since it's storing a dict, not numbers.

so you could work around by doing this:

h = arrays['header'][()]

The mysterious indexing gets the one value out of a 0d array:

>>> h
{'POSITION': (23, 54), 'TIME': 23.5}

Answer 2

As in @askewchan's comment, why not np.savez( "tmp.npz", data=data, **d ) ?

import numpy as np

data = np.arange( 3 )
time = 23.5
position = [[23, 54], None]
d = dict( TIME=time, POSITION=position )

np.savez( "tmp.npz", data=data, **d )

d = np.load( "tmp.npz" )
for key, val in sorted( d.items() ):
    print key, type(val), val  # note d.TIME is a 0-d array

---

This is not your question at all, but the following little class Bag is nice, and you can bag.<tab> in IPython:

#...............................................................................
class Bag( dict ):
    """ a dict with d.key short for d["key"]
        d = Bag( k=v ... / **dict / dict.items() / [(k,v) ...] )  just like dict
    """
        # aka Dotdict

    def __init__(self, *args, **kwargs):
        dict.__init__( self, *args, **kwargs )
        self.__dict__ = self

    def __getnewargs__(self):  # for cPickle.dump( d, file, protocol=-1)
        return tuple(self)


d = Bag( np.load( "tmp.npz" ))
if d.TIME > 0:
    print "time %g  position %s" % (d.TIME, d.POSITION)