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))
deb
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,)
and the array would be of object
type instead of float. the only way for this to work is having same sized arrays.
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)
but you would have to decide how you do this padding.