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

问题描述

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

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)

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

我假设我需要将我的数据展平成类似的东西:

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

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

我尝试了一个列表理解，它通常适用于列表列表，但正如预期的那样没有奏效:

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]

最好的方法是什么?

推荐答案

你可以使用 numpy.concatenate，顾名思义，基本上将这样一个输入列表的所有元素连接成一个单一的 NumPy 数组，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()

如果你希望最终输出是一个列表，你可以像这样扩展解决方案 -

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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