How can I check whether a numpy array is empty or not?

You can always take a look at the .size attribute. It is defined as an integer, and is zero (0) when there are no elements in the array:

import numpy as np
a = np.array([])

if a.size == 0:
    # Do something when `a` is empty

One caveat, though. Note that np.array(None).size returns 1! This is because a.size is equivalent to np.prod(a.shape), np.array(None).shape is (), and an empty product is 1.

>>> import numpy as np
>>> np.array(None).size
1
>>> np.array(None).shape
()
>>> np.prod(())
1.0

Therefore, I use the following to test if a numpy array has elements:

>>> def elements(array):
    ...     return array.ndim and array.size

>>> elements(np.array(None))
0
>>> elements(np.array([]))
0
>>> elements(np.zeros((2,3,4)))
24

https://numpy.org/devdocs/user/quickstart.html (2020.04.08)

NumPy’s main object is the homogeneous multidimensional array. It is a table of elements (usually numbers), all of the same type, indexed by a tuple of non-negative integers. In NumPy dimensions are called axes. (...) NumPy’s array class is called ndarray. (...) The more important attributes of an ndarray object are:

ndarray.ndim
the number of axes (dimensions) of the array.

ndarray.shape
the dimensions of the array. This is a tuple of integers indicating the size of the array in each dimension. For a matrix with n rows and m columns, shape will be (n,m). The length of the shape tuple is therefore the number of axes, ndim.

ndarray.size the total number of elements of the array. This is equal to the product of the elements of shape.