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 causesTraceback (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.
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, ndarray
s 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.
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