将列表转换为NumPy数组 [英] Issue converting list to NumPy array

问题描述

我有一个包含2000行和88200列的列表:

I have a list that consits of 2000 rows and 88200 columns:

testlist = list(split_audio_to_parts(audio, self.sample_rate, self.audio_index))

调试testlist输出给出

[array([-0.00683594, -0.00689697, -0.00708008, ...,  0.        ,
    0.        ,  0.        ]), array([-0.01287842, -0.01269531, -0.01257324, ...,  0.        ,
    0.        ,  0.        ]), array([0.02288818, 0.01940918, 0.01409912, ..., 0.        , 0.        ,
   0.        ]), array([0.00772095, 0.00671387, 0.00695801, ..., 0.        , 0.        ,
   0.        ]),

，依此类推. split_audio_to_parts是一个功能:

and so on. split_audio_to_parts is a function:

def split_audio_to_parts(x, sample_rate, audio_index):
for i, row in audio_index.iterrows():
    x_part = x[int(row['start_samples']):int(row['end_samples'])]
    yield x_part

当我尝试使用samples = np.array(testlist)或samples = np.asarray(testlist)将其转换为numpy数组时，尽管调试显示testlist包含2000个条目(具有88200个位置)，但它却给出了形状数组(2000).为什么这样?我正在使用64位numpy和64位Python 3.6.5.

When I try to convert it to numpy array using samples = np.array(testlist) or samples = np.asarray(testlist), it gives me array of shape (2000,), although debugging shows that testlist consits of 2000 entries with 88200 positions. Why so? I'm using 64bit numpy and 64bit Python 3.6.5.

推荐答案

问题是testlist是不同大小的数组的列表.例如，检查此代码:

The problem is testlist is a list of different size arrays. For example checkout this code:

>>>import numpy as np
>>>import random 
>>>random.seed(3240324324)
>>> y=[np.array(list(range(random.randint(1,3)))) for _ in range(3)]
>>> y
[array([0, 1, 2]), array([0, 1, 2]), array([0])]
>>> np.array(y)
array([array([0, 1, 2]), array([0, 1, 2]), array([0])], dtype=object)
>>> np.array(y).shape
(3,)

，数组将是object类型，而不是float.唯一可行的方法是使用相同大小的数组.

and the array would be of object type instead of float. the only way for this to work is having same sized arrays.

如果您确实需要将这些行以某种方式填充到数组中，则可以用零填充，例如:

If you really need to stuff these rows somehow into an array you can pad with zeros, for example:

>>> size = y[max(enumerate(y),key=lambda k:k[1].shape)[0]].shape[0]
>>> z=[np.append(x,np.zeros(size-x.shape[0])) for x in y]
>>> z
[array([ 0.,  1.,  2.]), array([0, 1, 2]), array([0, 0, 0])]
>>>np.array(z).shape
(3, 3)

但是您必须决定如何进行填充.

but you would have to decide how you do this padding.

这篇关于将列表转换为NumPy数组的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！