保存并从字符串检索Numpy数组 [英] Save & Retrieve Numpy Array From String

问题描述

我想将多维Numpy数组转换为字符串，然后再将该字符串转换回等效的Numpy数组.

I would like to convert a multi-dimensional Numpy array into a string and, later, convert that string back into an equivalent Numpy array.

我不想将Numpy数组保存到文件中(例如，通过savetxt和loadtxt接口).

I do not want to save the Numpy array to a file (e.g. via the savetxt and loadtxt interface).

这可能吗?

推荐答案

您可以使用 np.fromstring :

In [138]: x = np.arange(12).reshape(3,4)

In [139]: x.tostring()
Out[139]: '\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00\x04\x00\x00\x00\x05\x00\x00\x00\x06\x00\x00\x00\x07\x00\x00\x00\x08\x00\x00\x00\t\x00\x00\x00\n\x00\x00\x00\x0b\x00\x00\x00'

In [140]: np.fromstring(x.tostring(), dtype=x.dtype).reshape(x.shape)
Out[140]: 
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])

请注意，tostring返回的字符串不会保存dtype或原始数组的形状.您必须自己重新补充.

Note that the string returned by tostring does not save the dtype nor the shape of the original array. You have to re-supply those yourself.

另一种选择是使用 np.save 或 np.savez 或

Another option is to use np.save or np.savez or np.savez_compressed to write to a io.BytesIO object (instead of a file):

import numpy as np
import io

x = np.arange(12).reshape(3,4)
output = io.BytesIO()
np.savez(output, x=x)

字符串由

content = output.getvalue()

给定字符串，您可以使用np.load将其加载回数组中:

And given the string, you can load it back into an array using np.load:

data = np.load(io.BytesIO(content))
x = data['x']

此方法还存储dtype和形状.

This method stores the dtype and shape as well.

对于大型数组，np.savez_compressed将为您提供最小的字符串.

For large arrays, np.savez_compressed will give you the smallest string.

类似地，您可以使用 np.savetxt 和np.loadtxt:

Similarly, you could use np.savetxt and np.loadtxt:

import numpy as np
import io

x = np.arange(12).reshape(3,4)
output = io.BytesIO()
np.savetxt(output, x)
content = output.getvalue()
# '0.000000000000000000e+00 1.000000000000000000e+00 2.000000000000000000e+00 3.000000000000000000e+00\n4.000000000000000000e+00 5.000000000000000000e+00 6.000000000000000000e+00 7.000000000000000000e+00\n8.000000000000000000e+00 9.000000000000000000e+00 1.000000000000000000e+01 1.100000000000000000e+01\n'

x = np.loadtxt(io.BytesIO(content))
print(x)

---

摘要:

---

Summary:

• tostring为您提供基础数据作为字符串，没有dtype或 形状
• save与tostring相似，除了它还保存dtype和形状(.npy格式)
• savez以npz格式(未压缩)保存数组
• savez_compressed将数组保存为压缩的npz格式
• savetxt以易于阅读的格式格式化数组

• tostring gives you the underlying data as a string, with no dtype or shape
• save is like tostring except it also saves dtype and shape (.npy format)
• savez saves the array in npz format (uncompressed)
• savez_compressed saves the array in compressed npz format
• savetxt formats the array in a humanly readable format

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