python - numpy.array() 是否等同于 numpy.stack(..., axis=0)？

Question

我以自己为例:

import numpy as np
arrays = [np.random.rand(3,4) for _ in range(10)]
arr1 = np.array(arrays)
print(arr1.shape)
arr2 = np.stack(arrays, axis=0)
print(arr2.shape)

我发现arr1和arr2的形状和内容是一样的。那么这两个方法(np.array() 和 np.stack(..., axis=0) 等价吗？

Answer 1

一般来说，你应该从两者中得到类似的东西，但会有一些边缘情况。例如，将参差不齐的列表传递给 np.array 将给出列表的 np.array，但 np.stack 将引发异常:

In [119]: np.stack([[1,2], [4,5,6]], axis=0)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-119-2ba66e6300d6> in <module>()
----> 1 np.stack([[1,2], [4,5,6]], axis=0)

<__array_function__ internals> in stack(*args, **kwargs)

    423     shapes = {arr.shape for arr in arrays}
    424     if len(shapes) != 1:
--> 425         raise ValueError('all input arrays must have the same shape')
    426
    427     result_ndim = arrays[0].ndim + 1

ValueError: all input arrays must have the same shape

In [120]: np.array([[1,2], [4,5,6]])
Out[120]: array([list([1, 2]), list([4, 5, 6])], dtype=object)