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NumPy save some arrays at once

I working on different shapes of arrays and I want to save them all with numpy.save, so, consider I have

mat1 = numpy.arange(8).reshape(4, 2) mat2 = numpy.arange(9).reshape(2, 3) numpy.save('mat.npy', numpy.array([mat1, mat2])) 

It works. But when I have two matrices with one dimension of same size it's not working.

mat1 = numpy.arange(8).reshape(2, 4) mat2 = numpy.arange(10).reshape(2, 5) numpy.save('mat.npy', numpy.array([mat1, mat2])) 

It causes
Traceback (most recent call last): File "<input>", line 1, in <module> ValueError: could not broadcast input array from shape (2,4) into shape (2)

And note that the problem caused by numpy.array([mat1, mat2]) and not by numpy.save

I know that such array is possible:

>> numpy.array([[[1, 2]], [[1, 2], [3, 4]]]) array([[[1, 2]], [[1, 2], [3, 4]]], dtype=object)

So, all of what I want is to save two arrays as mat1 and mat2 at once.

like image 295
zardav Avatar asked Feb 01 '16 14:02

zardav


1 Answers

If you'd like to save multiple arrays in the same format as np.save, use np.savez.

For example:

import numpy as np  arr1 = np.arange(8).reshape(2, 4) arr2 = np.arange(10).reshape(2, 5) np.savez('mat.npz', name1=arr1, name2=arr2)  data = np.load('mat.npz') print data['name1'] print data['name2'] 

If you have several arrays, you can expand the arguments:

import numpy as np  data = [np.arange(8).reshape(2, 4), np.arange(10).reshape(2, 5)] np.savez('mat.npz', *data)  container = np.load('mat.npz') data = [container[key] for key in container] 

Note that the order is not preserved. If you do need to preserve order, you might consider using pickle instead.

If you use pickle, be sure to specify the binary protocol, otherwise the you'll write things using ascii pickle, which is particularly inefficient for numpy arrays. With a binary protocol, ndarrays more or less pickle to the same format as np.save/np.savez. For example:

# Note: This is Python2.x specific. It's identical except for the import on 3.x import cPickle as pickle import numpy as np  data = [np.arange(8).reshape(2, 4), np.arange(10).reshape(2, 5)]  with open('mat.pkl', 'wb') as outfile:     pickle.dump(data, outfile, pickle.HIGHEST_PROTOCOL)  with open('mat.pkl', 'rb') as infile:     result = pickle.load(infile) 

In this case, result and data will have identical contents and the order of the input list of arrays will be preserved.

like image 155
Joe Kington Avatar answered Sep 22 '22 07:09

Joe Kington