使用序列请求的数组设置数组元素在 1 维后具有不均匀的形状检测到的形状为 (2,)+ 不均匀部分
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【中文标题】使用序列请求的数组设置数组元素在 1 维后具有不均匀的形状检测到的形状为 (2,)+ 不均匀部分【英文标题】：setting an array element with a sequence requested array has an inhomogeneous shape after 1 dimensions The detected shape was (2,)+inhomogeneous part 【发布时间】：2021-07-14 22:04:23 【问题描述】：import os
import numpy as np
from scipy.signal import *
import csv
import matplotlib.pyplot as plt
from scipy import signal
from brainflow.board_shim import BoardShim, BrainFlowInputParams, LogLevels, BoardIds
from brainflow.data_filter import DataFilter, FilterTypes, AggOperations, WindowFunctions, DetrendOperations
from sklearn.cluster import KMeans
#Options to read: 'EEG-IO', 'EEG-VV', 'EEG-VR', 'EEG-MB'
data_folder = 'EEG-IO'
# Parameters and bandpass filtering
fs = 250.0
# Reading data files
file_idx = 0
list_of_files = [f for f in os.listdir(data_folder) if os.path.isfile(os.path.join(data_folder, f)) and '_data' in f] #List of all the files, Lists are randomized, its only looking for file with _data in it
print(list_of_files)
file_sig = list_of_files[file_idx] # Data File
file_stim = list_of_files[file_idx].replace('_data','_labels') #Label File, Replacing _data with _labels
print ("Reading: ", file_sig, file_stim)
# Loading data
if data_folder == 'EEG-IO' or data_folder == 'EEG-MB':
data_sig = np.loadtxt(open(os.path.join(data_folder,file_sig), "rb"), delimiter=";", skiprows=1, usecols=(0,1,2)) #data_sig would be a buffer
elif data_folder == 'EEG-VR' or data_folder == 'EEG-VV':
data_sig = np.loadtxt(open(os.path.join(data_folder,file_sig), "rb"), delimiter=",", skiprows=5, usecols=(0,1,2))
data_sig = data_sig[0:(int(200*fs)+1),:] # getting data ready -- not needed for previous 2 datasets
data_sig = data_sig[:,0:3] #
data_sig[:,0] = np.array(range(0,len(data_sig)))/fs
############ Calculating PSD ############
index, ch = data_sig.shape[0], data_sig.shape[1]
# print(index)
feature_vectors = [[], []]
feature_vectorsa = [[], []]
feature_vectorsb = [[], []]
feature_vectorsc = [[], []]
#for x in range(ch):
#for x in range(1,3):
#while x <
#while x>0:
x=1
while x>0 and x<3:
if x==1:
data_sig[:,1] = lowpass(data_sig[:,1], 10, fs, 4)
elif x==2:
data_sig[:,2] = lowpass(data_sig[:,2], 10, fs, 4)
for y in range(500, 19328 ,500):
#print(ch)
if x==1:
DataFilter.detrend(data_sig[y-500:y, 1], DetrendOperations.LINEAR.value)
psd = DataFilter.get_psd_welch(data_sig[y-500:y, 1], nfft, nfft//2, 250,
WindowFunctions.BLACKMAN_HARRIS.value)
band_power_delta = DataFilter.get_band_power(psd, 1.0, 4.0)
# Theta 4-8
band_power_theta = DataFilter.get_band_power(psd, 4.0, 8.0)
#Alpha 8-12
band_power_alpha = DataFilter.get_band_power(psd, 8.0, 12.0)
#Beta 12-30
band_power_beta = DataFilter.get_band_power(psd, 12.0, 30.0)
# print(feature_vectors.shape)
feature_vectors[x].insert(y, [band_power_delta, band_power_theta, band_power_alpha, band_power_beta])
feature_vectorsa[x].insert(y, [band_power_delta, band_power_theta])
elif x==2:
DataFilter.detrend(data_sig[y-500:y, 2], DetrendOperations.LINEAR.value)
psd = DataFilter.get_psd_welch(data_sig[y-500:y, 2], nfft, nfft//2, 250,
WindowFunctions.BLACKMAN_HARRIS.value)
band_power_delta = DataFilter.get_band_power(psd, 1.0, 4.0)
# Theta 4-8
band_power_theta = DataFilter.get_band_power(psd, 4.0, 8.0)
#Alpha 8-12
band_power_alpha = DataFilter.get_band_power(psd, 8.0, 12.0)
#Beta 12-30
band_power_beta = DataFilter.get_band_power(psd, 12.0, 30.0)
# print(feature_vectors.shape)
# feature_vectorsc[x].insert(y, [band_power_delta, band_power_theta, band_power_alpha, band_power_beta])
# feature_vectorsd[x].insert(y, [band_power_delta, band_power_theta])
x = x+1
print(feature_vectorsa)
powers = np.log10(np.asarray(feature_vectors, dtype=float))
powers1 = np.log10(np.asarray(feature_vectorsa, dtype=float))
# powers2 = np.log10(np.asarray(feature_vectorsb))
# powers3 = np.log10(np.asarray(feature_vectorsc))
print(powers.shape)
print(powers1.shape)
超级困惑。当我运行我的代码时，我不断收到此错误：
ValueError：使用序列设置数组元素。请求的数组在 1 维后具有不均匀的形状。检测到的形状为(2,) + 不均匀部分。
追溯：
文件“/Users/mikaelhaji/Downloads/EEG-EyeBlinks/read_data.py”，第 170 行，在 powers = np.log10(np.asarray(feature_vectors, dtype=float)) 文件“/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/numpy/core/_asarray.py”，第 102 行，在 asarray 返回数组（a，dtype，copy=False，order=order） ValueError：使用序列设置数组元素。请求的数组在 1 维后具有不均匀的形状。检测到的形状为(2,) + 不均匀部分。
如果您对为什么会发生这种情况有任何想法/答案，请告诉我。
提前感谢您的回复。
【问题讨论】：
首先，请发布带有行号的完整回溯。否则，我们只能猜测您的代码的哪一行引发了ValueError。其次，不要只是将整个代码粘贴到这里。尝试创建一个minimal, reproducible example。
我很抱歉。现在会这样做。
@jjramsey 我只是让代码更简洁一些并添加了回溯
它无法从feature_vectors 生成数字数组，可能是因为列表大小混合在一起
【参考方案1】：
这是一个产生错误消息的简单案例：
In [19]: np.asarray([[1,2,3],[4,5]],float)
Traceback (most recent call last):
File "<ipython-input-19-72fd80bc7856>", line 1, in <module>
np.asarray([[1,2,3],[4,5]],float)
File "/usr/local/lib/python3.8/dist-packages/numpy/core/_asarray.py", line 102, in asarray
return array(a, dtype, copy=False, order=order)
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2,) + inhomogeneous part.
如果我省略 float，它会生成一个对象 dtype 数组 - 带有警告。
In [20]: np.asarray([[1,2,3],[4,5]])
/usr/local/lib/python3.8/dist-packages/numpy/core/_asarray.py:102: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
return array(a, dtype, copy=False, order=order)
Out[20]: array([list([1, 2, 3]), list([4, 5])], dtype=object)
【讨论】：
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