NumPy 一次性保存一些数组

问题描述

我处理不同形状的数组，我想用 numpy.save 保存它们，所以，考虑我有

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]))

它有效.但是当我有两个具有相同大小的维度的矩阵时，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]))

导致
回溯(最近一次调用最后一次):文件<input>"，第 1 行，在 <module> 中ValueError:无法将输入数组从形状(2,4)广播到形状(2)

并注意由 numpy.array([mat1, mat2]) 而不是由 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]]])数组([[[1, 2]], [[1, 2], [3, 4]]], dtype=object)

所以，我想要的是同时将两个数组保存为 mat1 和 mat2.

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

推荐答案

如果您想以与 np.save，使用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，可以展开参数:

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，不会保留顺序.如果您确实需要保留顺序，您可以考虑使用 pickle 代替.

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

如果您使用pickle，请务必指定二进制协议，否则您将使用ascii pickle 编写东西，这对于numpy 数组尤其低效.使用二进制协议，ndarray 或多或少会选择与 np.save/np.savez 相同的格式.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，并且将保留输入数组列表的顺序.

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

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