Add metadata comment to Numpy ndarray

TobiasR's comment is the simplest way, but you could also subclass ndarray. See numpy documentation or this question

class MetaArray(np.ndarray):    """Array with metadata."""    def __new__(cls, array, dtype=None, order=None, **kwargs):        obj = np.asarray(array, dtype=dtype, order=order).view(cls)                                         obj.metadata = kwargs        return obj    def __array_finalize__(self, obj):        if obj is None: return        self.metadata = getattr(obj, 'metadata', None)

Example usage:

>>> a = MetaArray([1,2,3], comment='/Documents/Data/foobar.txt')>>> a.metadata{'comment': '/Documents/Data/foobar.txt'}

It sounds like you may be interested in storing metadata in a persistent way along with your array. If so, HDF5 is an excellent option to use as a storage container.

For example, let's create an array and save it to an HDF file with some metadata using h5py:

import numpy as npimport h5pysome_data = np.random.random((100, 100))with h5py.File('data.hdf', 'w') as outfile:    dataset = outfile.create_dataset('my data', data=some_data)    dataset.attrs['an arbitrary key'] = 'arbitrary values'    dataset.attrs['foo'] = 10.2

We can then read it back in:

import h5pywith h5py.File('data.hdf', 'r') as infile:    dataset = infile['my data']    some_data = dataset[...] # Load it into memory. Could also slice a subset.    print dataset.attrs['an arbitrary key']    print dataset.attrs['foo']

As others have mentioned, if you are only concerned with storing the data + metadata in memory, a better option is a dict or simple wrapper class. For example:

class Container:    def __init__(self, data, **kwargs):        self.data = data        self.metadata = kwargs

Of course, this won't behave like a numpy array directly, but it's usually a bad idea to subclass ndarrays. (You can, but it's easy to do incorrectly. You're almost always better off designing a class that stores the array as an attribute.)

Better yet, make any operations you're doing methods of a similar class to the example above. For example:

import scipy.signalimport numpy as npclass SeismicCube(object):    def __init__(self, data, bounds, metadata=None):        self.data = data        self.x0, self.x1, self.y0, self.y1, self.z0, self.z1= bounds        self.bounds = bounds        self.metadata = {} if metadata is None else metadata    def inside(self, x, y, z):        """Test if a point is inside the cube."""        inx = self.x0 >= x >= self.x1        iny = self.y0 >= y >= self.y1        inz = self.z0 >= z >= self.z1        return inx and iny and inz    def inst_amp(self):        """Calculate instantaneous amplitude and return a new SeismicCube."""        hilb = scipy.signal.hilbert(self.data, axis=2)        data = np.hypot(hilb.real, hilb.imag)        return type(self)(data, self.bounds, self.metadata)