NumPy一次保存一些数组

问题描述：

我正在处理不同形状的数组，我想将它们全部保存为numpy.save，因此，考虑到我拥有

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]))

有效.但是，当我有两个具有相同尺寸的一维矩阵时，它不起作用.

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]))

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

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)

请注意，此问题是由numpy.array([mat1, mat2])而不是numpy.save

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

我知道这样的数组是可能的:

I know that such array is possible:

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

所以，我要做的就是一次将两个数组另存为mat1和mat2.

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

答

如果要以与 np.savez .

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

例如:

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']

如果有多个数组，则可以扩展参数:

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]

请注意，订单不会保留.如果您确实需要保留订单，则可以考虑改用pickle.

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

如果使用pickle，请确保指定二进制协议，否则，您将使用ascii pickle编写东西，这对于numpy数组尤其无效.使用二进制协议，ndarray或多或少会出现与[c7>/np.savez相同的格式的泡菜.例如:

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)

在这种情况下，result和data将具有相同的内容，并且将保留数组输入列表的顺序.

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

NumPy一次保存一些数组

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