展平NumPy数组列表? [英] Flattening a list of NumPy arrays?

问题描述

看来我有NumPy数组列表(type() = np.ndarray)格式的数据:

It appears that I have data in the format of a list of NumPy arrays (type() = np.ndarray):

[array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), 
array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), 
array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]), 
array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]),
array([[ 0.00353654]])]

我正在尝试将其放入polyfit函数中

I am trying to put this into a polyfit function:

m1 = np.polyfit(x, y, deg=2)

但是，它返回错误:TypeError: expected 1D vector for x

我认为我需要将数据拼合为类似的内容:

I assume I need to flatten my data into something like:

[0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654 ...]

我尝试了一种列表理解方法，该方法通常适用于列表列表，但按预期的方法却无效:

I have tried a list comprehension which usually works on lists of lists, but this as expected has not worked:

[val for sublist in risks for val in sublist]

做到这一点的最佳方法是什么?

What would be the best way to do this?

推荐答案

您可以使用 numpy.concatenate 基本上将此类输入列表的所有元素连接到单个NumPy数组中，就像这样-

You could use numpy.concatenate, which as the name suggests, basically concatenates all the elements of such an input list into a single NumPy array, like so -

import numpy as np
out = np.concatenate(input_list).ravel()

如果希望最终输出为列表，则可以扩展解决方案，例如-

If you wish the final output to be a list, you can extend the solution, like so -

out = np.concatenate(input_list).ravel().tolist()

样品运行-

In [24]: input_list
Out[24]: 
[array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]]),
 array([[ 0.00353654]])]

In [25]: np.concatenate(input_list).ravel()
Out[25]: 
array([ 0.00353654,  0.00353654,  0.00353654,  0.00353654,  0.00353654,
        0.00353654,  0.00353654,  0.00353654,  0.00353654,  0.00353654,
        0.00353654,  0.00353654,  0.00353654])

转换为列表-

In [26]: np.concatenate(input_list).ravel().tolist()
Out[26]: 
[0.00353654,
 0.00353654,
 0.00353654,
 0.00353654,
 0.00353654,
 0.00353654,
 0.00353654,
 0.00353654,
 0.00353654,
 0.00353654,
 0.00353654,
 0.00353654,
 0.00353654]

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