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我正在使用 MNIST 数据集的一个子集，我想在其中规范化数据集中样本的特征。我正在尝试以 .mat 文件的形式加载数据集。谁能指导我如何将 .mat 转换为 numpy 数组，以便我可以执行平均和标准等基本操作。特征向量的偏差？

这是我加载 .mat 文件并转换为 numpy 数组的代码：

import scipy.io
import numpy as np

train_0 = scipy.io.loadmat('data/training_data_0.mat')
train_1 = scipy.io.loadmat('data/training_data_1.mat')

test_0 = scipy.io.loadmat('data/testing_data_0.mat')
test_1 = scipy.io.loadmat('data/testing_data_1.mat')

# to return a group of the key-value
# pairs in the dictionary
result = train_0.items()

# Convert object to a list
data = list(result)

# Convert list to an array
numpyArray = np.array(data)

print(numpyArray.mean())

但是执行后我收到此错误：

  numpyArray = np.array(data)
Traceback (most recent call last):
  File "<input>", line 1, in <module>
  File "/Applications/PyCharm CE.app/Contents/plugins/python-ce/helpers/pydev/_pydev_bundle/pydev_umd.py", line 197, in runfile
    pydev_imports.execfile(filename, global_vars, local_vars)  # execute the script
  File "/Applications/PyCharm CE.app/Contents/plugins/python-ce/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "/Users/mish/Work/ASU/Fall20/CSE 569/main.py", line 20, in <module>
    print(numpyArray.mean())
  File "/usr/local/lib/python3.8/site-packages/numpy/core/_methods.py", line 160, in _mean
    ret = umr_sum(arr, axis, dtype, out, keepdims)
TypeError: can only concatenate str (not "bytes") to str
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1 回答 1

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您将元组列表（键，值）传递给numpy.array，您已经使用了 numpy 数组train_0['<some variable name here>']

要获取变量名，只需使用：print(train_0.keys())

这可能会回答您的问题：将加载的 mat 文件转换回 numpy 数组

scipy.io.loadmat 返回一个字典：

Returns
    mat_dictdict

        dictionary with variable names as keys, and loaded matrices as values.

https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.loadmat.html

于 2020-10-15T13:07:46.227 回答